{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "# Load environment variables and set up auto-reload\n",
    "from dotenv import load_dotenv\n",
    "load_dotenv()\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "attachments": {
    "d63282d4-d236-4425-9d5f-7885573f2989.png": {
     "image/png": 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"
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u4XNDHjjGVvIi7C52/esD8s4z1VqNnId85Wqa7HPn0kmsneKBl4/uGe1Xtf0AVGzREzFixDDYR547jtbRfOhMBPoOxvm9Gw327zR5NbIXKm3w2MUDm7FzyWR8eP1CEjDFjhly5EPsOHEQO248xIkbH3HiJxD+GytOXCFRf5Z8xbW3+WzRLxGQPxxquXiEoXuxqeTrvwSFT2YCTIAJ2JmA/H7GIp2d4fN0TAAAi3R8GTABJsAEAIhCnSOJdPxQqM1L9+9e9fDganiRJfKgI086antXzRLENmqWhHNSXjsSsA76z7NooSRcUaVJY23PihnYvWyaRWP9Wac16vcaqyfUff38EZ71wj3nqKVM/zuSpvofSPwz1QYtP4IU6TLpdZnbp4Fe9VtLDEydKRs8luyzpCv3cVACWhbpxAiTNl4L4FK6uoMSZrOZABNgAsYJiN8xZ3atgUe3QoVwVwp75cYEmEDkE2CRLvIZ8wxMgAk4CAES6lzy5Bas1aJbv9x7o1/ffgh+4SBgo5GZty8eB4kLYuu/eC/S/JZd+PHqqf34d3g76diQlceQLE0Go3QO+M3FjsUT9Y6nzZwTydNkwOtnYVJhCupEglnfBbsQJ158vXPuhZ4DCWLy9lfTLvijZGV8evcaF/ZtwsUDWxTHW46Yg/x/1VZ89vbFE0xoUcLqHS3v2g013IbonbdqbHcEH9xq9XjEoN/CcK9Ebs5HgB4Oe3VwBf0++fn5CQUktNTECBOqsl2/Ukm+F2tpc9gWJsAEbEZA6/dimy2UB2ICGiNgkUgnVhM8dTbcM4AbE2ACTMBZCbRu6YqrV65g+/btcHFx0dQyxQfDCQv8gCzaemjVFKgoNEYeCpqtYEnQQ7zY1AIXJZyncFFD7eH1YMzuUUdxqFT9dqjcuo8i99yXj+/h1SCv1K/XnK2gMFF5+/H9G2b1qKOoLttxwnLkLPqXoh9VcKNcc2JLljo9hqw6rujz7P5NTHMznJu2cJVGKFGrJf6XJTceXLuIxUNaSedS8Yzh/mf1lkr2Xz21D9+/fYP/pL6KuSu27IkfP36A7P/54zt+/vgJyvcXJ35C5PmzstnceVF4GfDUNiCwZa43jqxfglGjRsHNzc0GI9puCLlIR7/n3JgAE2ACzkpg5VBXXDqjzRcmzsqc18UEWKTja4AJMAEmICPQxd0NZ8+c1rz3Bj8Yau+yff7wNqZ2qCAZRrnaClasrzB0XLMieP863AWyUqveqNrOQ28h6sIT1KGxxxQUq97M4KLFfDF0sOv0QGR2Karod3bXOqyd0l/6rGxjd9TuMkJvrMe3QjGjaw3F5xOC7ip+vn/1POb0Uq6JOhgSHFd4dxYKVIjNe1Mo4sZPaHTjJrYsiTfPHwnHKYcd5bLjFn0J7F7uiz3Lp6Nv377o16+fpkCwSKep7WBjmAATiEQCWk49EInL5qGZQJQSYJEuSvHz5EyACWiNAIt0WtsRx7FH7YnW2ccPXz59xIfXz/Hpw1t8+fgBxzctlUQ6taeduFKq4OrTvry0cPJQazbI1yCInz9/Ylj1LNKxLtMC9AoqrJ8+FCe3rZL6eAYGI37ipNLP714+xcmtq0CiiLwVrFAPzYfNUnx24+xhhYccHWwxfDYKlK+rZ586XJfCUylM1ViTi43WFNZwnCuELbWGAIt01tDivkyACTCByCHAIl3kcOVRmYApAizS8fXBBJgAE5ARYJGOLwdrCZDnG+VzWzO+l7WnYszW64gdJ67iPPI+Iy80sXX1XYfMeYsZHJtCQYfXDM95R42EwawFlOF38kIW/8uWB33m7cDnD+9w89wRnNsTqPB2E8eh8NRec7cjaap0Jm0rVKk+XIfMNGjbuT3rFSGsbhNXIkeRsgb7fvv6BSPr5JKOmRrXash8gkMSYJHOIbeNjWYCTMDJCLBI52QbystxCAIs0jnENrGRTIAJ2IsAi3T2Iu0885zavgaBvoMjtKDuMzfgtz8KK84VxQnxwzFbriF23HgGx//+7T+MqJVDOuY+ZQ2yFSwl/UwVYofXyKY4N2eRcrh+9pBRe/OUrIJ6PUYbzPmmFt7U88kHvX7mIJYMbSN91GzwdBSu3NDgvJ/ev8HoRgWkY1RdtkHvcRFiyic5BwEW6ZxjH3kVTIAJODYBFukce//YesckwCKdY+4bW80EmEAkEWCRLpLAOvGwh9YuwLaFhgUl8khLni4TkqRIg0TJUyFu/AQ4uuFfiUadrqNQppEyKf7SkR1w5cReoc/veQqj24wNRun99+UzRtUNr0hMTe2tRqGs45sXt4h+lnwlhMIUxrzdaJATW1Zgw8zh0njdZ23Eb7kLGRw/7MYlzOquqw5b030YqKKsofb+1XOMc9Xl0jOWN8+ihXAnpyDAIp1TbCMvggkwAQcnwCKdg28gm++QBFikc8htY6OZABOILAIs0kUWWecd927Iaczr11haIFVhLdfYHUlTp0es2LH1Fi4vkJC3THW09lyg6CMPTyXhrMu0tUbh/fflE0bV/UM6rq7aqq4oa2igknXb4M/arUChsOaaWpA0VE1WHOP1k4eY1Ka0NGTZRp1Qu+tIg1O8eRaGia10HoCVWvZC1fYDzJnDx52YAIt0Try5vDQmwAQchgCLdA6zVWyoExFgkc6JNpOXwgSYwK8TYJHu1xlGtxHIs4w8zMRmrkDC2ikeOLsrQOgeL0EieG64hBgxYkrnLxvlhtDju4WfU2fKBo8l+4wiVReZ6DBuKXIV11WYVYfDigNRSGuRqo2Ru0RFxImXwOIt279mDnYumST1N+VJ9/XTB3jWd5H6FihfBy2G/21YpHv+CCReiq1K2/6CVx+36EuARbrou/e8cibABLRDgEU67ewFWxJ9CLBIF332mlfKBJiABQRYpLMAEneRCHz5+B5eDfJKP4uFGUwhUoeMUiEHuRfbxlkjcHzzcmkIrw0hiJcwscEhj21cik1/j5KOGSrOIPfco44j1p5DomQpjZr45dMH3Dp/VLApRbpMin6HAhZi24KxJueTnyCv2Jopd0H0mLXJ4LzvXj7D+Oa64hjk3Ve/l24evuSiHwEW6aLfnvOKmQAT0B4BFum0tydskfMTYJHO+feYV8gEmIAVBFikswIWd8WZoLUI8NGFZdbqPALlmribJKPO1UYhoBQKKra9q2Zh178+0s/qEFbxAOVx82n/F0hUE5v7FD9kK6is7rpkSGtFoQjKcUe57gy1D29eYF6/Jnj+4JZwuPe8HUgvC4M9sXUlNswYJp3acsQc5P9Ll3dOPeaUduXw8tE94WPyGvTaeNngvOoCF+RB2G/RbsSMGYuvsmhKgEW6aLrxvGwmwAQ0RYBFOk1tBxsTTQiwSBdNNpqXyQSYgGUEWKSzjBP3Cifw7/B2uHpqv4Rj0PIjet5nalbfv33DiFrZpY/VHmY3zx/FokEtpOMp0/+O3nO3K7zpnj24hTXje4EEP3nr6rsOmfPqPNLoWPDBrVg1trvUjfLgkbgWM5YyX97D68FYM6G3JNDRCTXchqC8azfp3EuHtmHlGN3PDftOQIlaLY1eDgsHuuLWhePScVNefOq+6rnFQT6+e41P714jVYYsfBk6MQEW6Zx4cw0s7efPn7gXehYxY8YE3RPlKQCiFwleLRPQFgEW6bS1H2xN9CDAIl302GeLVnn1yhWkSZMGKVOlsqg/dXr//j1CL4cgb778SJgwocXncUcmoFUCLNJpdWe0Zxc9VA6rrhOKzFVila9AXsGVPh+49BBIjKP28+cP+LQvL3mg0WfkWVaoUgPET5QE9y6fwcUDWwwC6T5zA377Q+klR15qvp2qKMQ38rYrUrWJICi+fHwflw5uVYiN4uAe/+xH6oxZpbluXzwO+sIuNiruQEUejDV5/j3q03/xXqT5TSdQys876D8P2xdNUAyVu3gF5CpeEfESJsKb549x7dR+UKEOap0mr0b2QrrCFNq7QtiiXyHAIt2v0Iv4uZ/fv0WsOHERJ158o4OQ9y7lu0yQOBlixIhh9WR0T3p69zpePLyDb9++InaceLh14RiObvhHGKta+wGoaOC+QtWsP7x5iY9vX+Lzh/f4+pns+IakqdIK989EySz//mq10Vae8CLsLp7dv4HnD2/j+QP6/y3h3k7MkqQkezMLL1SMeTVbOR13ZwKRRoBFukhDywMzAaMEWKTji0MgMHa0FzZuWC/8e+euvRYJdT9+/ECj+nXx8OEDpEyZElt37EJsA5UMGTETcCQCLNI50m5Fra30wDiqbm7JiHo9x6BUvbYWGXVq+xoE+g6W+qpDWo9vXoaNswxXQjU1Qd8FQUiXRWeT2JfErX+Gt7PINrFTq5Fzka9cLcU55ME3rWNF6bMyjdxQp6suJ556gj3Lp4PEFrFRTjrykjHUfnz/JgiAoghnzlhzAqG58/m4tgmwSGff/SExafW4npJ3rqHQ/fevX2DxkFZ4fCtUMI5C2N19/JAxZ36LjKXf8XO7A7Hfb67ipYH65MTJU2G4/1nhYxIEN8wYihtnD4PmN9XIntINOqBc086CGBYVjThSugJjL1LUNjX2mIJi1ZtFhak8JxOwiACLdBZh4k5MwKYEWKSzKU7HHIy84Sr+VUYyftKUqahUuYrZxTx58hh1alaX+s1fuBhFiirDrMwOwh2YgMYIsEinsQ3RuDl+E3vj/N6NghdHrznbBE83SxoJfHP6NBAedsmTggo+xE2QSDqVvPT2r56NIFluOkPjUv47KuYgtsErjiF52gwGTXhw9QLIg8/cgy49IHcYvwwZcuTTG4cesie0KCGNYa4K6+PbVzCji+7vxKjAiyYfnt++eIL104fgyom9JjEmS50eXXwDzIYWW7IX3EebBFiks+++zO/fFHcunVRM6rn+kuKednjdQmydryzoQuHwFJpurtHvNomA6jmMnTd68xWh8rQhD1tzc5FYR+KXqXyZ5saw9jjds6ny9QG/uVad6lK6Gtp46e7hVp3MnZmAHQiwSGcHyDwFE1ARYJGOLwmEPXyI+nV13hJjxo5HjVrGE4GLyO7fvyd40oltss80VKxUmYkyAYcmwCKdQ2+f3Y0n0erVkwcg0Sh23HhWzU9hWq+fmj6XxKqQIzuEXE0UHkaNRLTcJSqhVP12oOqyCwc2l+Y1J4JRFdXLR3fi/pXzuHv5DN69eIIkqdIJ1V5TpMuIP/6sjFzFK5gU0igH34nNy5E6U1YhJM2cx8qpbatx+VgQ8pWtiaIWeozQHKHHdgl2vnh4Wwi9S5gsJTLmyIffXYqgUMUGiJ84qVW8ubNjEWCRzn779d+XTxhV9w+9CdWFaFZ4d0bIkZ2KfgXK10GL4X+bNPbpvRuY06ueosgNnUBiGt1/xEI18kEGLz+K5OkyQp0HU+xD90G6J3z7+gUfXr/QG5v6qStnRybRw4GLsHXeGMUUtL7iNVsg9W/ZkCz1/4RjVPAn7GYI7oacwdvnj1CnuxcKVqgXmabx2EzglwiwSPdL+PhkJhAhAizSRQibc510984dNGlUX1qUpSIdhbk2qKsT80aPHY+aFoh7zkWPV+NsBFikc7YddZ71UA4oKvYgzwG1e9k07FkxQ1rkuB23uCKq82x5tF4Ji3T22/5Ht0Ixs2sNvQnVIfzjmhXR88TNkq8Eukxba9RY8qCb06s+3jx/JPUh8apuD28UrtxQuKc9u38T/45or8jDKRbhUYfYUxhu2cZuisIS5MV2N+QU9q2ajWunD0jzUC5PEuqsfYFiLfnbwSewwEMZskqefLS+WLHjWDsc92cCmiLAIp2mtoONiSYEWKSLJhttapk3b9xA82aNpS6Wim2PHj1Cvdq6L3UjPb1Rr34DJsoEHJoAi3QOvX3Rzvgp7cpJD7b5ytVEq5Hzoh0DXrBzEmCRzn77Gnp8N5aNctObsGTdtqjfK9w7jMQ2CnVXNxLCPJbsM2gseRrP7dsIFGovNhLous3cgHSZcynOofnJDrF5BgYL3rJP7lzF9M7VpM8b9Z2I4rV01a/lg5DNSgHgAAAgAElEQVR38upx3RXefl2nByKzS9FIhSmmPRAnUecYjdTJeXAmEMkEWKSLZMA8PBMwQIBFOr4scOPGdbRo1kQi4T1mHGrVrmOWzLOnT1GrRlWp37ARI9GwkW4cswNwByagQQIs0mlwU9gkgwRO7/THuqkDpWNNPKZYHE7KSJmA1gmwSGe/HTq2aRk2zdYvVEPVk6mKMjUq3EBFI6hReL/oGUeim9fGywaNVY9LfTtP9TeY71Ke704eQht24xJmdddFbTQdOA1FqupeLKsnfhF2R6iOLba63b1RukH7SIUp9zA0JVpGqhE8OBOIJAIs0kUSWB6WCZggwCIdXx56Ip2n12jUqacLfzWG6MWL56hRVZeDbvCQYWjSzNUk0a9fv+DM6dMIDb2MN6/f4PXrV3j9+jVevniB79+/Y/LUaciU6TeLduVySAjOnD6Fa9eu4vLlELx/9w75CxREteo1UKVqNcSMGdOMLV/h77cGwRcvoHKVqsJ56vbgwX08f/4cL54/x5s3b1C8RAn89tvvFtnHnRyTAIt0jrlv0c1q+QOzuPYhq44LD8/cmIAzEGCRzn67uG3BWEUBGnFmeZXVI+uXYMtcb+EQ5VC7sH+TZOC47TeFsFV5M+R5Z8qrjbzgLh7YjI9vX+HPOq0RO05cYTi1SNd82CyzOdzkohmFnDYbPD3SYKrX+b9seYQQW1u2108e4srJvXh08zIeXLso5OnMmCu/kJuUWJH4aa4FH9wq5Pej6t8VmnfX2y/KlffqyX0hZx4VF6Kco1nz/6k3LHlHvnh0D0mSp7Y4L+jXzx9x89wRJE+XCemz5TFp6s+fP3D15D5hnWHXL+H+lXNCUaXMeYuBPDup0JK5dv/qeVAFdbqGKjTvgaSp0ilOoYrBLx7ewbtXz/D+1TMhHJrzAhqnyiKduSuOjzMB2xNgkc72TB1uRLUn3Sgvb9StZz5slcS1qpV0bysHDh6CZq76IQiUK+Tw4UPYHbQT27ZuMcmnbbsO6NWnr8k+nz9/xpzZs7B61Qqj/bJmy4apvjNMCmr+fqsxZdJEaYyDR44jQYIEoBx9G9avQ1DQTjx98kQxx++ZM2Pdet0XU4fbbDbYLAEW6cwi4g6RTIAeaOiBiirGqh+SPr1/I1QPVFcQpPAvCgPjxgSchQCLdPbbSXm4Jokhd0NOS5OP2XJNEDECpw8BFYGhVr3jIOxcMlnqM3LdBSRMklxhcNA/U7Bv9Wzps6LVmqLJAB+rF6XOl9d61HzkLav/UlU+8IyuNYTK2dQsKWxhtVGyE+h+7VlPKTyZCsm1Zi76/nx6+xqBvbFGAl3zYbPxx5+VjPYJuxGCWd11BeI6+/gha4GSoL8ntKfBh7YpQpLFgYauOoGk/1/wgj6jquTLPTvh+tlDgjDY1XcdSJQ01X78+C6cI1bs7rtwl16os3g+iZGBvoOF8Y01qthLXuPyaujyvmTj5DalpdyJVdt5oFKr3iBx8cK+TYIQbKh6uCXXlTV750x9WaRzpt3ktTgKARbpHGWnItHOWzdvwrVpI2mG4SM90aCh7mdjU7998waVK/4lHTYk0r19+xaeI4fh8CHjf3Dl45O45h+w3uhqqVhFj65dQP811xImSoRFi/9Bzly5DXb19hyJLZt1gtuKVX44dPAA5s+bY3LojZu3IUPGjOam5+MOSoBFOgfdOCcymwpBUEEIahQ6lbdMdcSJGx9P7l7DtVP79aoYkmcBVWGM7OToToSYl+IABFiks98mLRzoilsXjgsTVmzRUyGuefyzH6kzZsW8fo0l8a7VyLlYOaabZOCAfw8gVYYs0s9ULXZcs6KKe1X/JfuQJlM2qxelzknXdvRi5ClZxeQ4ck86UaSxemIrTpjbpwHuhZ5TnEH37WI1miPNb9mFyq7W3p+//fcVK7zcQZWuLWnkLUheg4bamaC1CPAZIB0iETFuwkRY7zvEYFVcsaN6TLUHtyUCKF1XdH2JrUHvcYL3n7rROv8d3s6SpSJT7oKgvH+GKourw50LVaqPMo06Yf30oYJXprFWrIYrGvfXCc8WGRJNOrFIF002mpepKQIs0mlqO6LGmPv37qFRg7rS5EOGjUDjJk3NGvPq1StUq1zB6Hk/fvxA967uQniruqVNlw7FihVHhgwZsGrVSnz88EHqcvjYScSLF8/g/H169cDRI4elY+TZ1r1HL6RKnRqXgoOxfOk/ePnypXScRL/VfgGIFSuW3nj9+/YWRDmxUd/bt26ZXff8hYtRpGgxs/24g2MSYJHOMffNmaxeO8UDZ3cFWLQk8rbrMi1AL5zHopO5ExPQMAEW6ey3OVM7VsTzB+Hff9qN+QdLR3aQJheLIMiFLwrnJG81sfWYvRmZchWQfj63OxD+k/tJPxeu0gjNBvlGaEHq6q7txy1F7uK6757qQR/fvoIZXapLH1MxHSqqE5mNwiupgq2pljZzTuQoXAa/uxSFS6mqiBMvgcn+B/3nYfuiCVIf8lyr7jYEGbK74PnD2zi+ebme95tYEVc98OHARdg6L7wACDX6u/Hy0T2zSNQCp9ojjwYw5EUpH5jEQRIJxUbXl9rr7/P7t5jYqqRCMKQ+ZRq6gcJfb54/quc9Xqp+O9TrMVpvDRQm+3dP3TONPH+iqQVnK1hSeNnFTZ8Ai3R8VTAB+xNgkc7+zDU346OwMNSro/sCYyxsVW24Oiedurrr1StX0LqlMkcdiX/t2ndE+gwZpOEo5JRCT8W2bccupEmbVo/T/n17MdBD96WvdJmymDjZRwhRFRvlkGvVwlUh+o0ZOx41aumSDot9O3VshwvnzxvcD5e8edG6TTsUKFgQmzduVHjXTfaZhoqVdLn4NLehbNAvEWCR7pfw8ck2IEBhWivHdpcemg0NSQ9s9AAl5G6Ka/ilhg1M4SGYQJQRYJHOfuiHVsssTTZo2WFMbltW+rlRv0koWLGeIqTTa0MIvBrklfqoq5muHtcDFw/o0pv0W7gbJFJFpL0Iuwuf9rqoDbeJK5GjiM4+9ZgUhrt/zd/Sx/0X7xW82SK7hRzegbVT+pv0TBNtIJHMdchMo/nVXj8Nw6TWpSSTKTdg91mbkCJdJukz8lYk8UReOddY2gPyzCYPbUONxq7Stj+y5C+B9y+fYdHgllK30g06oG53L+lnChmlCr+Us05spkJ7P394B++G+RTTUpERdQ69LfNG40jgYqlflTb9UKl1H8SIEUP6jPiuGN1FMdbApYcEwVHeDOVrlR+v3LoPchYrj9QZs2Bs0yLSIS74Yfw3hEW6yL578PhMQJ8Ai3R8VeDZs2eoVV0XOtDPYwBatmpjloy6uqu6Kuyypf9g1gxdsl63Tp3RtXsPvXGpAES7NrovBfsOHkHixIkV/SgvR51a1RU54rZuDwJ55Mkbee8NGtAfB/bvkz42Jjo2blgP9+7e1bOnS9fu6ODWSfK+27tnNwYP9JD6+c6YjbLlypnlwx0ckwCLdI65b85mNeXxuX3xBG6dP4qn92+AHtqSp80g5PKhB85cxSsYDPVxNg68nuhLgEU6++w95fAaVVeXFmRU4EUsGdpGEn9I1ChUuSGmdgj3XiMxo9+i3RheQxe6Ki/mQJ5P3g3ySWIViXMk0kW0qQUrqjZLVWcNNfIu2zhrhHSIQk5bey6I6NRWn/fqyQOc37Mel4/tMpjjTT1g/V5jhGII6qb2PmvrvQh5SlXV6yeviEsHja1309+jcGzjUr3zKb8bhZ8mTJpCOPbu5TOMb66LFPmrWVfU7DRUcR7lQ92xWJf/lHIYUm46Q00dZlusejM09pii6KoOT82QIx96zNqoV9jiy8f3glgrFwh7zdmGDDl0YjENTMUx5KHY4mR0HbYYOkuRQ0/uQUrz9pqz1eo9jw4nsEgXHXaZ16g1AizSaW1HosAeddgqFW6gAg7m2v3799Covs6lfNyESYoKqYsWzFd4oP1ZshT69O2HHDlzKd6O0Tx7du8ShLVSpcugpgGvt8ePH6FuLV1oRfsOHdGjVx/JRBLnTp86ib9nzwSJfvLmtzYQ2bLrv0UtX660wuOOzjHkdXfnzm00baQrpLFj1x6kSpXaHB4+7qAEWKRz0I1js5kAE3AqAizS2Wc73z5/jAktdVU8x+24JeQqO73TXzCgSNUmKFG7Jeb1Dc9VnLNIOXScuAJy7zu52ES5M6e76wSlso06oXbXkRFejLp6KolGxWo2lwpVkHfX49tXcWr7aiEEVN7IKzDF/36L8Ny/ciLllCPR7sntq7hx7jBObDFc7GzwimPCCxh5m9iyJN48fyR8RPnXesxSFiyjkF4Khz23R5nDuWHfCShRS/fSWxxTXhhE/Iz6UX95U3vKGQpNJZGMQp/lTZ2TUDwmz2NInxmq7nth30asmdBbGk4dzkweg+SVuWPRBIVARx6Ag1cel6oAiwNQVVcqPiFvVNyChES1Bx+FZFNoNjVDguSv7L8zncsinTPtJq/FUQiwSOcoOxWJdr579w6VyutCB7r16ImObu5mZ7x+/Rpauupy102aMhWVKus88tQecuKAKVOmFHK6FS1aDAULF0b27DkQM2ZMk/MdP3YMvXp0lfpMmzELZcuWA1WmPXhgPwLXBehVYqXO5BXXqbPSPV4cpHiRgoo5TfXdvm0rzpw+hdp16qJwkaJm2XAHxyXAIp3j7h1bzgSYgPMQYJHOPntJ4fVifjkSMSgc8eDa+di+cLxgQJZ8JVC2cSes8O4s/EyiXdOBUwWhRvRqonBJ8rijpg5LlHvZRWRFH968UIQlyscge7980uU0lh+r3WUEyjY2/102IjZF5BxitW/VLBzd8I/idJGn+CGtx6u+i9Tnr6ZdUNN9mCDaXTu5Hye3rzbopUfiaftx/+p5oNFAlGNQXtHUVF8qgEGCJ3nIkeeboabOm1q1/QBUatlL0VWdS5AKHHWbsUFvOHUVYPLkjBs/Ee5dPi1UnT0bFGBwj42FPR8KWIhtC8ZK85CY12vudoN5W0mgPhiwQPBKp2tcLeJFZJ+d8RwW6ZxxV3lNWifAIp3Wd8gO9n3+/BnlSuveopKoRYKVuRYcfBEd2+nCYqf6zsBf5XXJfMm7rWe3Ljh16qTJoagKa8OGjdCgUWNkyZLVYN9VK5fDd6qPdIzy0ZFA9/TJE4P9acx+/TyEMQ21r1+/okzJ4tKhjBkzYW3gBsSJE8fcsvm4kxNgkc7JN5iXxwSYgEMQYJHOPttESfkXDWohTEb5vSjPV+ixXVjm2Un4jBLvV2zZExtmDhd+rtC8O6p3HAx5qKA8d9mpbasROH2IZHynSauQvXCZCC+Gigp4N8pv8fkktLgOmWEwPNTiQSKxozpElUSk4f5npRnVhQ/oeOKUaUFiqrFWrom7kKPUWDGK+f2b4s4l3XfxiFbaFecnIY8q2oqNrhvyposRQ/fCffMcTxzd8K/Uh8KOKRxX3ZaNckPocV04NFWMvXpyn1HxlcJWG/YZL4jHhpq8OjodbzLAB0WrmS+GF4lb7vBDs0jn8FvIC3BAAizSOeCm2drk//77D6X/1OWgaObaApTHzVxT52qbM38hihdX/tEkoY76Baz1M1jlVT2Ha/MW6OcxUK8a69jRXti4QenWb8g+EudatGiFlq3bIGnSpEaX8PbtW1SuoMsrRzn4KBcfNybAIh1fA0yACTCBqCfAIp199uDC/k1YMz7cC0oMrXx67wZ8O+kKZFVs0RP7Vs8W+tTp5okyDTsKIg2JNdQKVaovFEKgtn/NHOxcMkkyXl351dpVff38UVG0wtj5JN5kK1AS5V2764WPWjtnZPankFISOOXVVeXFFCiE1X9SX4tMoKq5FVv2QppMuvyAhk4kT0lR5PvVHIHi+LO610bYjUvSdPLiIe9ePsX45roX4STieSzZZ9DLTx7aa2rRNEaF5j1QtFoTg+OI55IHKHmCim3E2nNIlCylRTy5k2ECLNLxlcEE7E+ARTr7M9fkjPLQTxLaSHAz1+bPmwPKOye2wA2b8dvvyipL8jHevnmDs2fP4NTJkzh+/KjBog3CF8B69eHppSyrbk6ko2qsTZo2Q9VqNRA/fnxzpkNd9IIKRXTvoXTVNzsId3BKAizSOeW28qKYABNwMAIs0tlnw6iqJlXXpJa7eAVQTrDv3/7DiFo5JAMoPPL62UPCz6JHlNwDSsxTR8e3L5og5EsTW9vRi5GnpC4VirWrUtvSoM94/FGiIj6+e4NvXz8L3ltpf8+BuAkSWTt0lPVXe48NXXUCSVP/T7DHnEhHno0l6rRC8RquSJIyrUVrmNKunCQKGspxZ9Egqk5qO8Vrh7pRYQkqMCG2pgOnoUhVw5Et5kQ6l9LV8GftVshZ7C+Fp54xm6lwiDw3offGyw51bURkLyL7HBbpIpswj88E9AmwSMdXhUCgWZOGuH3rlvBv8kbbvfeA2dDPfn164vCh8C9t1A4dPWGRQCb2f/niBQ4fPoR1Af56xR727D+k8IRbvGgB5s35W7FbVNm1Xv0GQrGKrFlNv0VUb3PYw4eoX7eW9DF70vEvgkiARTq+FpgAE2ACUU+ARTr77IFcUClcuSGaDZ4uTCwPZ5VbIlbUlFcgpcT8febtELqpPemqdxwkeEBFtFG12GHVdalQtJZrLiLrUgtTY7fdQKzY4elWbgefwAIPZS44CuEtWLE+ClVugCz5ilskVsntks9nK086Ek+ntC0nFbig+SiMlrzWxjTW5XwmUXHgskPS+tS8Fg50xa0LxxUfk5BIufqo+iyF+1rT1k0bhNM7/KRTRqw9i0TJrBvDmvmiQ18W6aLDLvMatUaARTqt7UgU2TN08EDs3hUkzT5xsg8qV9Ev9y52UFc8NeR99ygsDFQB9o88LiZDTykklqrEPnz4QJp/6fJVIO84sVHhhlEjhkk/d+7STSgIESNGDKPEQkMv4/379yhUqLCe4Ei57GrXrCada8h7L4q2gqeNYgIs0kXxBvD0TIAJMAEALNLZ5zJQVLj8/yIFNDOFwFIorLpRYn9KtL91/lhQfjVqYsEJ+veVE3uwdGRH6bRwkeYwYsWObXZBn96/waObociUuwDixk8o9ZdXkqUCFVSoQivtx4/veHb/plBt1hLPtofXgzG7Rx3J/NSZsgmhoGKjirCT2+hy+JGXInkjxo4bz+iSXz95iMd3riJz3qLC3qib3JNOnQPvVziSxxp5romtdIP2giC2a+lU6bMGvcfhzzqtjU6jFtW6TAsQhEhjjXjfOn8MCZIkQ8ac+rkKKXeivJLugH8PIlWGzL+yzGh/Lot00f4SYABRQIBFuiiArsUpd+7YjhHDdHno/vgjDxYs/gcJEiTQM/fnz5/o0bWzoiDESE9vwatNbPKiElmzZcO8+YuQMpXhN1l379xBk0b1pXPJky9o9z7Ei6f7QnLxwnm4dWgn9SlVqjRm/q1zpVcbudZ/DSZPDC8tT5524ybo8qPQZ+qKthUqVsKUqb5a3Bq2yc4EWKSzD3CqYHfl+G7hDfqTu9dQvGZzTu5sH/Q8i5MR+O/LJ2ye641n924iS75iyFawFHIUKWfyJZYjIGCRzj67REUjqHgEtTpdR6FMIzfh33tXzcKuf3UFu+gzuRhHOeqoMqfYxm67KQhxL8Luwqf9XwrjG/WdiOK1wotTGGrf/vuKYxuXYs9yX6FggDzHHfWXi3QkBNXt7m0fOGZm+fb1C/7uXV/K99Z73g6kz5bH6Fmvn4ZhXt9GCu+zah0GgnL+ie37t28YUSu79DMxH+Z3WiFayieQF3GgvG1kg7pKqTp/3ISguzbhR/eecc2KGi3yQILgoOVHESee8TQ0as/Lmp2G4q9mXQ3aR/n8/Cb2wcUDW4TjDftOQIlaLRV91aG2ouenTRYcTQdhkS6abjwvO0oJsEgXpfi1M/nHDx/QtElDRbXUosWKYarvTCRKpMvz8eTJY4wb7Y1jx8K/0FEjj7dFS5YqvNWWLf0Hs2aEh0xQMySqkQdd0I7tmDBhHGh+sVHxiAGDlIUrqG/zZo2lkFzqq/a2o8+oauuSRQtB4bHydvzUWUUxChIaSxQtJHWhtc5bsFg7G8KWRBkBFukiHz09VPhN7K1InE0PFZ4bQhxeWIh8ejwDE1ASuHv5jPDgL2+UH6pR/8lImiqdw+Jikc4+WycPa202yBdUjIBayJGdWOHdWWFEtoIl4T4lPJTwzE5/BEwdKB2nqrAkElH7d3g7XD21X3Fuq5HzkK9cTcVnJPJcP3NQ8MqTF1Ig77shq3QhkHKRrmCFemg+bJZ94JiZhTzYJrUpLfWiv2PtxixB1gIlFWfSd056KbVx1kiFQEdedD1mbUL8REkU/Tf9PUoQLcVmLMRXXvRD7Nt1eiAyuxRVjLd0ZAdcObFX+kwUVG0BUZ7TUD2eJaHJb56FYWKrUtKptPe95+8QPBPl7d3LZ1g/fYiiEmyuYuXRYfwyRT919dzOPn56+2GLdUenMViki067zWvVCgEW6bSyExqw49y5s+js1kHPEgplzZotO+7evYMTx48pjpPX2xq/AKTPkEHxuTo8lQ62a98Rf5Uvj48fPyH0cggCAvwVoqA4wBr/dcieQ5ewWPx8V9BODBsySDEPhb3my58fVKGWxgxcF4CXL18q+tSpWw+e3mP01kXhrhT2Su33zJmxbr1+WIcGtoVNsDMBFukiF7ihhwqaMXPeYujquy5yJ/+F0ekh617oWcSMGVOogEjJyp25PXtwC2+fP8bveQojTjylR/WTO1exc8lkvHr6EOTZQN4kXz99wPvXLwQk5D3h7uMvJHPnFvkEPr59hTFNdC+dxBlJMOjx9xazlR8j38KIzcAiXcS4WXvWuGZFpN9deZGH5w9vY2qHCorhSjfogLrdvYTPbpw9jMVDWknH3SauRI4iZYWf1dVhxU7ZC5UWPD3fPHuEe1fOSR5oapubeExB0eq6vGxykY7G6DR5tbXLjJT+9HdhUqtSCuGNJvrjz0rIkq+EUAzixcPbCDkapLdW+v3sOWcrUmfU5dsTjVSLf/R5sRquyF28IuIlTISnd6/jdNBavTFJ4Bq0/LBe9dPA6UNwapuO2bA1pywKzbUEGgmtFJ4r3v/l95+hq08iXsLEZodRF3ugdZRv3l34G/L+9XPB01NuvzhgkwE+eh745/duELztxNZq5FzkK6fLQW3WGO6gR4BFOr4omID9CbBIZ3/mmp5RXbHVnLEUIkqhoupGnnE1a1RVeMiZG4sEv5mz5qBgIf2HDTr3+/fv6NW9qyLM1tyY5ME3dsIkgznxunZ2w5nTp4UhaO4Dh3TegebG5ePOS4BFusjbW3lYjjgLhTW5lK4uPNwZyqWjtubz+7eIFSeuyfAZCpeipNY0nqm8lcZWSjlv6CHoxcM7+PbtK2LHiYdbF47h6IZ/hFOqtR+Aii31q0H/9+UzPrx5iY9vX+Lzh/f4+pns+IakqdIKHiZaTV796vF9PL1/E58/vBXW9/XTRwT6Dhb+TfmQOkxYphAl1Q9UhjhWbtMXVdr0+6WLicTAzx/fI13mXHqeJr80sBOeTHmsrp7chwv7NuHOpZPSCum66zF7s55XiiMgYJHOPrskD4WUh2vSfXB4DWVRLtchM1CoUnhqk7cvnmBCixKSkeTdRl5uYqMKr1Tp1dpG+eYo75zY1IUj5EUqrB07MvrT79v8/k2tGpoEulaj5iFnUWVYsHyQPcunC3kZLW0kbHUYvxTpsuTWO0Udutxn/k78L+sflg5ttt+p7WukvxliZ2v+BlAY8N896+gJfaYmLu/aDRQqHDNmLEU3deGN+r3GomTdNmbXwB2ME2CRjq8OJmB/AizS2Z+5pmeksNJNGzfAd5qPSYGNxK9effshZ85cRtdz6OAB9O/b26L1kjA3cNBQ5P7D9JeGb9++wXeqD/z9zL9FpbDZfh4DFWGucmP+nj0T/y4JD3Flkc6ibYoWnViki5xt/vr5I6a0Lav4Ek5hQX/8WdmiCcmrY/W4ngi7cUnoX6vzCJRr4q44l97kk2fH41uhwuf0IOTu42cwubShSckr7NzuQOz3m4vnD8KrXRtq8sTbJAhumDFU8CpRexKozyV7yBOlXNPOFgmSFoH5hU43zx0B5ZUS81EZG4oq9qXJpHtY37typiIxuKHz6vUcg1L12kbIOnoo95vQR5G0nnJQUS4qZ2kkgIQc3iE8YOYqXl7PW/FX1rltwVgcCghP6E+tQPk6aDFcWR39V8a317ks0tmHtJjDi0Iv+y/eq3ixsX76UJzctkq6n3r8cwBJUqaRDBOLTtC9jQQ+MdxV7BB6bJfg1UT3SXONxLf6PUcLHmjqJi98oEWv6wfXLgrrNPV3Q1wTiUt/Ne2ChElTmEOCM0FrQVV0zTVi1tpzntEXQddO7cc/w3V5nfsuCDIo5pmbx9hxeik2za2SImR5uN8ZJE6R2uIh3796jhWju+BuSPjLc1NNHpat7vfx3WtFdVlzhSvMzcXHARbp+CpgAvYnwCKd/Zk7xIxv375FwFo/XAoOxtWrV4S8dKlTpUaOnLlQukxZlCylyx9hakH3793DmtWrsGXLJj3RjwpKFC1aDI0aN0HOXPpv/kyNe/LEcZw7ewbBwcGgIhXx48VDqlSpheIUBQoWRLlyfyGPi646rKGxnj17htkzp+PVy5eoXbceqtdQ5kpxiI1iI21OgEU6myMVBlR7VRgS2UzNTJ4Kcg8h6uu5/pLCw0qdi4b60ANRDTdljktD85BXCImA6jmM2TR68xVBWImItwg90Db2mIL8f9WOHNhmRqUk7STkyHMemTpFHsZG/cg7MPRYkPBARmG/MWLFRNj1Szi3Z700jKmHKHOLNvRgSsxGrD1nssKhuXG1dPzCvo1YMyH8JRYJG/TQrA4rjqi9FIJHOcGunT4gDUHedJlyFYjokFFyHot09sFO18ud4BPIlLuQnocyvbig0NUf378jzW/Z9K5ROv749hCo900AACAASURBVFVBjDGW/5DuEyRI3wk5BXoxIAp25PmVLM3/kK1gaeQuUUFIeWAsjQC9eDkTFICESZOjcJXGSJ5WmWLFPqRMz0L3Rcqvd2HfBjy9d1MIc6WWMVd+pP09F9Jmzok8JatYbfvj21eE3+V7l89IAlbCZCmFtALkNUdjEkNT1XPppQClKHhw9Tyy5v8TlVr30fNA+1WG5ClPf1fIm7x0/fYoVV8nClo6Nol9wQe3gkRPEuue3buB+ImSIkmqtEiSIo3gefhHycpIkS6TySHpbwi9cEvxv99Qw22wZr3YLeUS1f1YpIvqHeD5oyMBFumi465HwZrpS+CbN2/w+vUrJE+eAsmSRSwMLQpM5ymjGQEW6Wy/4SQKjW1SSHo4C6/4dsRiUYJy3oyqq+9lSwnMKZG52CjJOSU7lzdLvIjoIXROr3p63h4kDCVJlc6gd8Tg5UeRPF1GXDq0DSvHdNODRmukBynK1/bh9QuDniR95u0AeY/Ys1HuOPI2pAcqdaOHSArzVTd5iJsxW6lK78KBrtJhQ0niLV0nJVc/vlmZDJzOtXWIlqX2REa/fatmIUhWOdPWa3t4PRize9SRTM9bpjpaeyoLKkXGumw5Jot0tqSpjbHouyDdE01V+9SGpWwFE2ACIgEW6fhaYAL2J8Ainf2Z84xMgAlomACLdLbfHHWOmOodB6NC8+4WT/ToVihmdq2h118dUilPgC52pjCgLtPWGp2LPOjm9KqvSPxN4lzdHt4oXLmhkID72f2b+HdEe0UoD4mM9DafCixM61hRGp88BMs2dlN4hNCD6d2QU9i3arbCu4nCy0ioix03nsUsfqUjeb0s93JXVPmj8Sj/U9nG7oJX4qf3b7B2cn9FBb1mg6cLLEw1dRL5dmP+EZKnR6SRN8qSococQoZC8SIytlbOObrhX2ye4ymZ033WRvyW23A+1ojaTKIpiadiG7Plmt2utYjaLD+PRTpbUOQxmAATYAK/RoBFul/jx2czgYgQYJEuItT4HCbABJyWAIt0tt/a3cumYc+KGdLA1noNhR7fjWWj3PQMK1m3Ler3Cq/crE5iLnYmccdjyT6DiyLRam7fRnhw9YJ0nAS6bjM3CMUK5I3mJzvE5hkYjPiJk4KKG0zvXE36vFHfiSheq4XB+SgcavW47gpvv67TA5HZpajtoRsYcfvC8Ti4dr7iiDrZOx08ErgYW+aNlvp1nLDcZIJz6nj11H4hxFJsnSatQvbCZSK0LgrN8pvQGxcPbBHOJ69E1yEzpcqRERpUYyed2emPgKkDJavkCfttZapaCOzs44esBXSep7aaJ7LGYZEussjyuEyACTABywmwSGc5K+7JBGxFgEU6W5HkcZgAE3AKAizS2X4b/+5VTxLC5EUXLJ3p2KZl2DR7pF737IVKo9Pk8CIyck8uynX05vkj4XMS3bw2XjY4lXpc6tt5qj8y5Min11+e704eQkuFLKg6otiaDpyGIlUbG13ai7A78GlfXjpur4IIYTdCMKt7LYVdjftPRrEauhBV8eD9q+cF70JqtF9DVp1ArNhxTG4XJYhf5tlJ6tPVd52QY+pXGlWdff/6uVCF0Fb52n7FHlueS3mXVo3VeZPaOpE72Uqhy77uVSSzqdouVVx0lMYinaPsFNvJBJiAMxNgkc6Zd5fXplUCLNJpdWfYLibABKKEAIt0tsVOoZ7DqmeRBqUQSAqFtKapq1WK58oFvyPrl2DLXG/hUMEK9RSVQcdtvymErcqbIc87U15t5AV38cBmfHz7Cn/WaY3YceIKw6lFOkOeaeq1ysNyKYyUwkkjs1G11Dm9Gyg8Bmu6DxMqDBprVPH17uUzKF7DFUlSpjVr3qVD27FyTFepX2SEb5o1wkgH8pS8dfE4Ht0MwYNrwfj8/g1+dymKAhXqCsU7qMKqqXZ883LcOHsImfMWlyoKkxfm9bOHhXyF714+FRhRYYbf/iikd60ZGlst0vVbtAdpf88R0SUaPI+u2RG1skvHLMnPaFMDfnEwFul+ESCfzgSYABOwAQEW6WwAkYdgAlYSYJHOSmDcnQkwAecmwCKdbff3/esXIFFKbJZWW5Vb4TexN87v3Sh8RN5ZVPVNbGKercDpQ3BqW7hXXfWOg4RKdmIbue4CEiZJrlhY0D9TsG/1bOmzotWaoskAH6sXr86X13rUfOQtq58/Tz7wjK41QNUKqdlDOFHneKNqohQCrBYurV687AQSMKk6rth6zdmGDDlMV9gW+1Ii+T0rpuN28EmhMiCJaP99+SyNlSpjVlDxCmtFLCo4svOfKUL4rrFGxTLaei9Cqgw6IVne98qJPVg6sqNiXe9ePUPAlP6ga1vdSPQjb0pDifHpWtkwYyie3LmmV0iEwrITJkmGmLHiIG78BML59P9YseMiS/4SKFa9WYS2R36tUZESyoHoKI1FOkfZKbaTCTABZybAIp0z7y6vTasEWKTT6s6wXUyACUQJARbpbItdHjpJI0ckvFOeAL9ii54Kcc3jn/1InTEr5vVrLIl3rUbOVVRcHfDvAYUIQ+LNuGZFFUJJ/yX7kCZTNqsXr85J13b0YuQpqQsxNDSg3JOuajsPVGrV2+p5rTlh6cgOimIRJEaSKGnLdm7PevhP0oVSWlO5lrz2Fg0ynMdPtNFaj8OXj+4JVWzpv+YahTl38V2H9AYq7arF3MJVGuHc7kCTQ5as2wb1e43V67Nr6VTsXTnTnDkGjw9bcxpJUqax+lz13k8Iumv1GFF1Aot0UUWe52UCTIAJ6AiwSMdXAxOwPwEW6ezPnGdkAkxAwwRYpLPt5lw+GiRUFBWbJeGgagumdqwohBVSo1BZEh7EJhY1kAtfJBCRB5HYeszeLIQiio1EFv/J/aSfSXhpNsg3QgtXV3dtP24pchevYHSsx7evYEaX6tLxViPnIV+5mhGa25KTXoTdhU/7v6SulK9v4LJDZnPMWTK2vM+ZoLUI8BkgfWRN+KahfHnq+eX5By2xjYpYUDELsZGnWvUOA5E4RRrcv3IeB/3nKjzhyKOOrhu1d+HGWSNxfPMyS6ZU9Bmx9iwSJUul+IzCZjfOGmH1WHTCcL8zSJwitdXnrps6EKd3+kvniQVPrB4oCk5gkS4KoPOUTIAJMAEVARbp+JJgAvYnwCKd/ZnzjEyACWiYAIt0tt2c83s3wG9iH2lQSyqFqi0YWi2z9NGgZYcxuW1Z6edG/SahYMV68KyXR/rMa0MIvBroQi3Vc64e10OqHEon9Vu4GyTSRKSpRTC3iStNViGlMNz9a/6Wpuq/eC/S/KbLGxYRG0ydc2LLCmyYOVzHy0T12V+Z+9T2NQj0Haxbl5WeiRT+++j2FcSMGVMQEGPEiIkNM4dJQhp5J5KXoiUt5MhOrPDuLHUl0bTlyLmIGz+h9Bnt26xuNRXelBRSW6hSA8UU8lBr+QHKh1ij01BkyVccCRInw/oZQ0F5+cTWxGMKiqpCVKlq7bVTB/Dp/Ruhyq4Y8kznkIdpzFgx8eP7D/z48Q0/v/8A5RIkDlkL/IlMuQtasnS9PuqKvkNXn0TSVOkiNJa9T2KRzt7EeT4mwASYgD4BFun4qmAC9ifAIp39mfOMTIAJaJgAi3S23ZyT21Zh/fSh0qDuU/yQrWBJiyeh3GSj6uaW+o8KvIglQ9tIRRAqt+6DQpUbYmqHcO818pjqt2g3htfQha7KvfdI+PBukE8SZ0icI5Euou310zBMal1KOp2qzZLXl6Gm9qTKW6Y6WnsuiOjUFp2nFiQNeXhZNJCZTup9VocYR2QOuQdloUr14TrEfKgoFSqZ1KqUVN2X5h2y6jjIg1DeSDBbOboryNNTbPV6jEap+u0U/dThonQwV7HyoGuKxDmxqXMTVmrZC1Xb6zwL1euX51CkY+N23DJbwCIiDNUhtmJ4eETGsvc5LNLZmzjPxwSYABPQJ8AiHV8VTMD+BFiksz9znpEJMAENE2CRzrabczhwEbbOGyMNaqqCqqGZ3z5/jAkt/5QOkZix3neIFMJXpGoTlKjdEvP6NhL65CxSDh0nroDc+65+rzEoWbetcPzJ3WuY7l5VGq9so06o3XVkhBetrhJbs9NQFKvZXCpUQVVAH9++ilPbV4NEOnkjr8AU//stwnObO9HWgqSp+dQee7YQ6eQhzMVquKJxf10xEGO2qEXTCs27o3pHnYcfiXO3zh/Dzn8mK6rd0nh9F+5Cusy5FEPLcx3SgQw58qHLVH/ETZBI0Y/2eXhNnUckVRgmIc9YI08/8vgTW2TliqMceCTUia33vB0Gc++Zu5ai4jiLdFFBnedkAkyACSgJsEjHVwQTsD8BFunsz5xnZAJMQMMEWKSz7eYcWb8EW+Z6S4N2nuqPrPl1opu52SgkUMwvRwn+vTZeFkIFKYyPWpZ8JVC2cScpvJFEu6YDpwoVZcXqm1Xa9gd53FELObwDK0Z3kaaNSI48uc0f3rzA2Ka66rXyY2Tvl08fDC6xdpcRKNtYl6vPHIeIHH//6jnGuRaVTv2zTms06D0uIkOZPYfytlH+NrHZQqTzqu8i8SvTyA11uo4ya4e6km27MUuQu0QlPLl9BZeP78bJLSsVXnbigPJrRD6Jr3sVPL17Xfqo74IgpMui8+yU953YsqQ0NlUh7uq7zqi9cvFPvK7NLi4CHUShSzzVmoIeEZjOpqewSGdTnDwYE2ACTCBCBFikixA2PokJ/BIBFul+CR+fzASYgLMRYJHOtjt6attqUGif2DqMW4pcJgorqGeXV/5Mmf53DFx6CKHHdmGZZyehK4UxVmzZU8q7JnpOyUMlSzfogLrdvYT+ans6TVqF7IXLRHjRn9+/hXej/BafT4IM5T7LU0rnzWfxyVZ2fHrvBnw7VZbOqtymL6q00RXMsHI4k92PbVqGTbNtK9LJvSErNO+B6h0HmTVZ7blJ+ejIk/HN80cGz6X9qN1lJIrXMlxdVi68kSDcZdpaozb83aue5J1H1yWF2RprJDyLOenE69rs4iLQQZ2TzhbiaQTMiNApLNJFCBufxASYABOwKQEW6WyKkwdjAhYRYJHOIkzciQkwgehCgEU62+70hX0bsWZCb2nQ+r3GomTdNhZPcmH/JqwZ30voT8nze8zaBLX4VLFFT+xbPVvoU6ebJ8o07Ii5fRrgXug54TN5PrP9a+Zg55JJ0vzqyq8WG/b/Hb9+/qgoWmHsfMp9l61ASZR37Y7kaTNYO02E+t+9fEYKA6YBKKyXwnsjox3buBSb/tZ5uvW3snCEIZvkIl15126o4aYTe42tYd20QTi9w8/sEkmco+ukbBN3RW459Ylyb74//qwkVBc21qiKsTzH3fidt4XCD4aaXET+X7Y8QmXZyGhqm7hwhG0ou7q64vjx47A2x6ZtZudRmAATYAL2I8Ainf1Y80xMQCTAIh1fC0yACTABGQEW6Wx7OTy4dhF/96wrDVqiVks07DvB4kmOBC7Glnmjhf7kFdV+3FJ8//YfRtTKIY1Beeiunz0k/EyFGKggw7JRbgg9Hl4QQsxTR//evmgCDvrPk86liqFUOTSiTW1Lgz7j8UeJivj47g2+ff0siDRpf8+hl8MsovNZc96VE3tBhQ/EVq6JO2p1HmHNEBb3VXvS/UrFXHFSuUgn94Y0ZZQ5kY6E3pJ1WqNAhbqIEy+B2fXJbXApXQ1tvBYaPUddDGLE2nNIlCylwf5T2pXDy0f3hGO/5ymMbjM2mLUlIh3kYd8kTHpuuGRUOIzI+JF5DnvSRSZdHpsJMAEmYBkBFuks48S9mIAtCbBIZ0uaPBYTYAIOT4BFOttu4X9fPmFU3T+kQSnxfq85Wy2eZMfiiTjgN1foX7hyQzQbPF34t9wTST5YrznbkCFHXgT4DMCZoPDQRLmnktqTjkIoKZQyoo2KMwyrnlU63R655iy1Ve1JJxcrLR3D0n7qnHR95u/E/7Lq9t3SceT95AIZhaM26jvR7DB7V83Crn99FP0o9LRYjWYoUKGeIJha2qhS7LDqWaTu5jzpgv6ZInl00kmGClGIg8lFOnNhtJbaq+738e0rjGlSSPqYqg5T9WFHaSzSOcpOsZ1MgAk4MwEW6Zx5d3ltWiXAIp1Wd4btYgJMIEoItGnZHFeuhGL79u1wcXGJEhuMTeqoIVbq5Ptjt91ArNhxLGLrP7kfzu0OFPr+1bQLaroPE/5NIbAUCqtuowIvCuGLW+ePxeF14V5P8sT8V07swdKRHaXTSMAZuOwwYsWObdaeT+/f4NHNUGTKXQBx4yeU+svFJCpQQUUItNDI3tGNCihMsTQMlaqVksiXOmNWJEmZ1uxyTm5bhfXTh0r9bFGgQM5VLtCaMubcnvXwn9RX6kI5+Cq17oMYMWIYPe3h9WB8/vAOWfIV17su5TaY83iTe33SZKbyL8pF5sjKSXfrwnEsHOgqrfuvZl1B1YcdpVHBGSo8M2rUKLi5uWnKbEe9F2sKIhvDBJiAQxBYOdQVl84ch5+fH0qWLOkQNrORTMDRCVgk0olfRuYtWIyixYo5+prZfibABJiAQQKJEsSHS57wyo13797VHCVfX19Mnz4dkVkAIDIWvW7qQJze6S8NTSGDFDpoSVs0qAWoeAQ1qu5JVT6pGfKYkotxlKOOPJvENnbbTUGIexF2Fz7t/1JMTR5axgoHUMdv/30F5Vzbs9xXqDYqz3FHx5Vhme1Rt7uumq0la4zMPvJwR5pHbbuhuSmv2tb5Y4RwTBIxByw9iNhx4po0k7wWyXtRbD3/3oKMOS0vqGFocHk+OAphplBmc03tPZirWHl0GL/M6GnyMN2CFeqBqv3Km9yG1JmywWPJPqNjyfMnUqd6PcegVL22BvvLw7GpAxWZINa2bJQjkK5bsf1qJWNb2mZurPypgF4dXHH7ojYfDOUiXf1KJRH8wtyK+DgTYAJMwPEIaP1e7HhE2WImYBkBFuks48S9mAATcHICJNB9+PQZxYsUFFbKIp3tNlydr8xc2KB8ZrnHUbNBvihcpZFwOOTITqzw7qwwMlvBkkIid2pndvojYOpA6ThVhSWPJWr/Dm+Hq6f2K85tNXIe8pWrqfiMQnWvnzkoeOWJ+cOog7pyp1ykMyT02I6k9SMdWrsA2xaOU5xYtjHlphuu8C4jz7mHNy5h5+JJkigqnjRo+RGkSJdJ+JHCe8NuhOC/L5+Fn2PEjIlYsWLj4oHNOBSgy9fWccJyZM5bTPBMixkrtklPNmOrkgtkYj5CcwR+/PiOGV2q4+nd61JXKjZCuejkjYTXfStnCmKvvI3bflOwV2zy608uAhuy43bwCSzwaCYdoiIdVKzDUNu7ciZ2LZ0qHSLRusWw2YgdN57qGvyMV4/vI3WmrAq7zHGga3dcs6KCqCw2W+QJNDevLY9rOcTK3d0dQUFBaOO1AC6lq9ty2TwWE2ACTEATBEigoxcQM7vVxKObl3HkyBFkyhT+XYAbE2ACkUuARbrI5cujMwEm4AAERIGOTGWRzvYb9u7lU4xvXlwx8JCVx5Asjfkqp3JPMHmRh+cPb2NqhwqKMeXFBW6cPYzFQ1pJx90mrkSOImWFn9XVYcVOlLMrW8FSePPsEe5dOYfHt0INwmjiMQVFq+vEGLlIp7W8X9++fgGFG8tFRloUVZt1KVVVKMJBVXDvhpw2uFYSRUkcFdv8/k1x59LJCF0kiZOnQmMPH5BIK7bXT8NwcO08vH7yEGSrvInFQOgzEsh+z1NEcTxZ2gyo291LEXpMHUgwXD2up6Ivhb3+9kchYb1UzOTk1pV4/1rp/lSkahM0HagTzmgAChelsFGxiR6ZhgC8CLsDn/blpUOmvBbVHn/inhSq1ADJ02TAhzcvcOfSKUGMpkb2kwetpU0d9mttLkhL57F1P/GhkMbVskhnyKs5b0og5KWtifB4TIAJMAH7E8iXCrj0/38ixe84Wnx5bX8yPCMTsA8Bi0Q68Y3hlKm+qFBR9+XaPibyLEyACTCByCMgF+gehYWhXp2ayJgxI44eDQ+x1FJbvHgxRo8ejTINO6JON0/JNPmDrZbslduyYeZwnNiyQvqoaLWmaDJAmeDfkO2zutdG2I1LwqHe83YgfbY8wr/JY2p4jWyKU1yHzACJHNTevniCCS1KSMfVoX5U4ZUqvVrbKN8c5Z0Tm7pwhLxIhbVjR1b/WxeOYeHA5lYPT2JayxFzpCqo6kq2Vg8ICJV35WGrao8ya8ckj72cRZXhy+QVuGRoGz2PQFNjU1gsXSOUz1De5DkR6fPh/mdBYqOhpi6SYs5jdOeSydi/5m+Lliz3EjV3wtdPHzCjaw2FMNtq5FzkK1fL3KmaOj65TRm8evIAwcHBSJo0qaZsc9TUA5qCyMYwASagSQJygY4MZJFOk9vERjk5AYtEOvHLSPOWreAxYJCTI+HlMQEmEF0IyAU6WvP+fXsx0KOfkBiXEuRqrR0/fhyUCyl9dhf0nrtdYZ7Whbpn929impvyJQ8JQPn/qm0Ss1jdlfKB9V+8VxE2SYUKqGABNfK08vjnAJKkTCONJwosdIwEPjHcVewQemwX/Cb2UYQEGjOGxLf6PUeDKnGqm7xSJ4V4dvVdp7VLR/AeXO7ljucPbpm1jXjV7eEthBbHjBlL0Z/GoJx1EW213IejXFNdmDIV96Bw4og2uibS/JZd7/Tv375h6/zRipxsxuYo3aA9ancZaTCc9NS21QicPkQ61XtTqJ7nnnzc1eN64OKBLcJH5V27oYab7lz1/GTjjkUTcDhwkdnltx+3FBTya0mT/15QfwrPHrT8sFXhspbMY8s+6ofCz+/fwrtReE5DLXpvrF27FgMGDBBya1KOTXnLmwoI4Rx1trw8eCwmwATsREB9L6YwVwp31erLazth4WmYgN0JWCTSiQ+GuXLnxsrVuuTfdreWJ2QCTIAJ2IiAWqCjYaf6TMaaVSvRt29f9OvXz0Yz2XaYzJkzCwN6BgYjfmKld4lLSuCyhsOtKIecGL5HayAxqN2YJchawHi1sJ8/f+JO8Alkyl0IceLFV8AkjykSn358/440v2WTPL7ETnT88e2rSJwiNZKmSmdwIygMNOTwDtwJOYWb545Igh0JG8nS/A/ZCpZG7hIVhPxqMWLENDgGhcWeCQpAwqTJUbhKYyRPaz6M17ZXhWWjffn4XqiIezfkjLDWN88fCSeSZ1jilGmR2aUoyKMsZ9FyeizlM1BY5/f//sNP+t+PH5SoDj9+/BDy1dHP4r/DP/+Onz9+IkGSZEiULKXePlBV1Qv7NoJCoslTj0RBIYddrFiIGTOm8O+YsWIhVqw4iBEzhvAz5cCj//7uUgSpMmQxuXgKe6ZccfdDz+Fe6FnhGqK1JkmeGr/nLYo//qyMTLmUFXDlA5J9u5f74s2zMBSp0hh5SlU1OR8VJjngP1fgULlVHyRPl9Hs5lD+vNM7/UBVZh9eCxZsjJ84GdJkyobf8hRGgfJ1zK6TJiH+h9ctxrYFStGzQZ/x+LO2LvTbrEEa6HD56E4s9+qs2RcmDx48QJkyZYR7MN2LuTEBJsAEHJ2AWqCj9YhVy5s0aYKpU5XpIBx9vWw/E9AyAYtEurdv3yJ//vA3mqfOXtDyetg2JsAEmIBZAoYEOjqpVYtmuHb1qqbLzNeoUQOhoaFCgQQKgVM3LQt1H968xKLBLfVyvZGXXKWWvaSiEGY3MJI6kCBIedHUYmAkTRflw1Lxh9hx4xoVH6PcQDbAIgJ03W6e44mzQQF6XqHFariiUb+Jmt1jQw+FtOgtc71xZP0STb8wyZcvH969eyd4NZN3s7qxR51Fly93YgJMQAMEjN2LRe95Hx8fNG3aVAOWsglMIHoQsEikIxTig+G8BYtRtFix6EGHV8kEmIDTETAm0NFCtVw0QtwIb29vLFmyREgiT8nkDTUtPxxSQnxKCC+vvklrUFdMdboLjxfEBCKJwKNboZjZtYbe6JT3sVH/SXohy5Fkhk2H1XLRCHGhYr5myq1JrLkxASbABByRgKl0KWJu0O3bt8PFRf9lhCOul21mAo5AwGKRTnww5Lx0jrCtbCMTYAKGCJgS6MR8dHny5MGOHTs0C3Dnzp3o3Lmzwbx0cqO1XGnw/avn2Dh7BC4d0uXV02LBBc1eBGwYE5ARIA/VsU0LK5hUbNETVdr202weOmNeG7QIeT46LRaNEEGLhXwMVQVW3Is5Rx3/vjIBJqBRAqYEOircQyJdkiRJcOlSeAEvbkyACdiHgMUinZgkl35R9x44bB/reBYmwASYgI0ImBLoaIqund1w5vRpTYdXkZ1iLiT6t7EwKxGZlj3qyEb6AvjkzlVQAv2s+UsgYdIUNtptHoYJRC8Czx7cEsLIEyZJjgw58+lVqXUkGpQDcM/y6ZrNRyeyvHz5MmrWrCn8OGj5EaRIl8mRMLOtTIAJRHMC5gqOrZ3igbO7AsD56KL5hcLLjxICFot0ZF3p0qXx8OFDeHqNRp169aPEYJ6UCTABJmAtAXMC3aOwMNSrE/6wpWXPDXHdHh4eCAgIgDkPDuqvdaHO2r3k/kyACTguAXMPhbQyMbxqwYIFqF69uqYXS9W2qbiaqfQD4gJMeQ9qepFsHBNgAk5HwNy9mDyaJ7UtI3g2c6ir020/L8gBCFgl0onedOkzZMCmLbowJQdYJ5vIBJhANCVgTqAjLN6eI7Fl8yaHeVso96azxIODhbpoevHzspmAgxE4E7QWAT4DkDFjRhw9elTz1pNAR0IdVXkdvOyIXsVtzS+ADWQCTCDaETAn0BEQR/FojnabxwuONgSsEumoyit501E1qylTfVGhYqVoA4oXygSYgOMRsESgk3vRHTlyBJkyOUbIkujBUaZhR9Tp5ml2c1ioM4uIOzABJhBJBCx5KKSpRS86R6okKEaZWOJNR2tkj7pIush4WCbABMwSsOReLPei8/PzE1IPcGMCTMC+BKwS6cg0X19fTJ8+XUgiuXK1P8irjhsTdVpuugAAIABJREFUYAJMQGsELBHoyOZWLZrh2tWrqFatGhYuXKi1ZRi1R/TgoA5tvBbApbT5sDB+OHSY7WVDmUC0I7BlrjeOrF/icEnKxSgT2jBzeUKj3abygpkAE9AMAUsEOjJ2uVdnXD66U/N5QTUDlg1hApFAwGqRjrzpmjVrhtDQUOTKnVsQ6rgxASbABLREwFKBzttrFLZs2ig8FFJoVdKkSbW0DLO2iLnpKNSKHg4tSVzOQp1ZrNyBCTABGxGw9KFQDHOlaR3Rc8Pd3R1BQUHCPZjuxXRPNtf4XmyOEB9nAkzAVgQsvRcfCVyMLfNGC9+L/f394eLiYisTeBwmwASsIGC1SEdjUz6kGjVqCGGvVECCCklwYwJMgAlogYClAh2JcyTSOepDocia7sX00iR9dhd0nuLHD4dauAjZBibABCwm8OjmZSwY6CokKB81ahT+j703gb9q2v//VxlDuRKiosGQopAhooy5krHIHDJkbDRcQynzULnmqQwRH0O5JCrTRdxkCg3mENG9pkKZ/4/n+v7W/q/P/uwzj/uc1/vx6MHnnLXX8Fzr7M9nv8576NevX9rXlktDvsDmXkxxtdYdO5sTr64pl6lpHiIgAlVOIF2B7uPZ/zG3n9XH0opTyoEq314tv0IJZCXSwWLq1KnmpJNOslgk1FXo6dCyRCBmBNIV6B6YcJ8Zdc1VdnVxfSh0W+N/aSKhLmYHVtMVgQolkMlD4fgRJ1qBLm4pB8JbN3fuXBtpwhfYpB84ZOg1+tKkQs+3liUCcSGQ7r2Y8NaHrhlq78XHH3+8GT48da7juDDQPEUgjgSyFulYrJ+Hg9DXa0Zdqxx1cTwFmrMIVACBdAQ6Hp5Gj7rahrhivXv3NqNGjYr96v2HQ8Ksjh5+u/XmSGUKt0pFSO+LgAgUigD558hDh22++eY2tCpuKQfCbPy/iwl9Pfqi262Xs0wEREAEik0gXYGO8FbCXLG4f1lSbMYaTwQKRSAnkY5J4VFHXiQefolfHz7iYtNt190KNV/1KwIiIAJ1CKQj0L3+2mtm9KirbJEIrNJc+RHqBg8ebENfMSq+dtqrd0pPDgl1+kCJgAjki0A6D4Xffb3QTL55pE1MjlWa1wb34hNOOMGGvvKlyZ5HDzJU4U5l6bBL1YfeFwEREAEIpHM/4V788DVDDGGu2MCBA82gQYMEUAREoAwI5CzSsQbCrfiDxD0cUvH1pJNPMT33278MlqgpiIAIVDKBVALdv59/ztw/4V6DSIc1a9bM3HHHHRWZDJe8SCNGjDAPP/ywXSsPiDsf1M8+ICZLZJ7OH3OVfIa0NhEQgcITIPcc3nMUicDsF7vDh5tDDjmk8IMXeQTuxRSToAo3hlddp+6HpLwXF3maGk4ERKACCaT6mw5Rjnux+6KEezF/F3funDoCowJxaUkiUJYE8iLSsTL+IBk7dqz9h1ed+wOs534HmF13281s02nbsgSgSYmACMSXQCKB7o3XX7MecxMm3GsWffllcD/iYZBvCeMeUpVqxwi5GjNmjPXkcMYDYrudupvWHTpHCnap/qhLNabeFwERqF4Cie4fCHOLPp5rhTnnrQElUg1QIKLSKwe6v4vdvZgvS7gXcx/Wvbh6Py9auQgUikCye/HHb//HCnPhezF/Fzdv3rxQU1K/IiACWRDIm0jnxkasIwQ2/IDI++St69RpO9Np223tN6jOJOBlsXO6RASqnMDcd982y3/51VLgiwFEuddfnxV4zDk83Gt4GORfpYtz4SPBvXjcuHGBN4d7H6+O1h13tHnr+H9ne2zbznz8a6MqP1lavgiIQCYEEOKW/7QkuIQHwC8/mms+fvsVm4Tcvxfvvffe9ouSansg5IsTBDsXceKYkK9ugzbt69yL12/dLmWqgkz2SG1FQAQqn8Dq/5tr3v2y9r2Y+zD34/C9mL+J+eK62u7FlX8KtMJKIZB3kc4Hwx8l5OZ45ZVX6vxhUikAtQ4REIHyI0AS8vbt21vX/UoMpcqUOCFX3If5rwu/yrQPtRcBERCBTAmQXsC/F1fbFyVhXtx/+fKEv411L870NKm9CIhAtgS4F++4447We5m/i6v9XpwtR10nAsUiUFCRzl8EHnZOsOO//OxMf6gUa7s1jghUDgE/dwZ/bPCHB//4I0R/fCTfZ+65c+bMsfdkcoo64zWXrqByTopWIgIiUEgCfCmy5pprBkNwb8Y7g3uxvDRS34v5AoX7sO7FhTyl6lsEKp9A1L2Yv4v5okT34srff62wsggUTaSrLGxaTTEIEKbHH63Dhg0rxnAaQwREQAREQAREQAREQAREQAREQAREQARKRkAiXcnQa+BkBBDnunTpYpvU1NSo4pCOiwiIgAiIgAiIgAiIgAiIgAiIgAiIQEUTkEhX0dsb38URjtenTx+JdPHdQs1cBERABERABERABERABERABERABEQgAwIS6TKApabFIyCRrnisNZIIiIAIJCNADtmRI0fanDYDBw4ULBEQAREQAREQAREQAREQgQIRkEhXILDqNjcCEuly46erRUAERCBfBPz78YwZM5SAOl9g1Y8IiIAIiIAIiIAIiIAIhAhIpNORKEsCEunKcls0KREQgSokoPtxFW66liwCIiACIiACIiACIlASAhLpSoJdg6YioIfCVIT0vgiIgAgUh4Dux8XhrFFEQAREIBmBqVOnmnnz5pnjjz/eNGrUSLBEQAREQAQqlIBEugrd2LgvSw+Fcd9BzV8ERKBSCOh+XCk7qXWIgAjEmcCWW25pyBE6bNgw069fvzgvRXMXAREQARFIQkAinY5HWRLQQ2FZbosmJQIiUIUEdD+uwk3XkkVABMqOwEYbbWTnRAGfQYMGld38NCEREAEREIH8EJBIlx+O6iXPBBYuXGi6dOlie62pqTGdO3fO8wjqTgREQAREIB0CEunSoaQ2IiACIlBYAhLpCstXvYuACIhAuRCQSFcuO6F51CHw0EMPWbd+ufTrcIiACIhA6QhIpCsde40sAiIgAo6ARDqdBREQARGoDgIS6apjn7VKERABERABEciKgES6rLDpIhEQARHIKwGJdHnFqc5EQAREoGwJSKQr263RxERABERABESg9AR8ke6dd95RVcHSb4lmIAIiUIUEJNJV4aZrySIgAlVJQCJdVW67Fi0CIiACIiAC6RMg/UCLFi2UHzR9ZGopAiIgAnklIJEurzjVmQiIgAiULQGJdGW7NZqYCIiACIiACIiACIiACIiACBgjkU6nQAREQASqg4BEuurYZ61SBERABERABERABERABEQgpgS22GILs3TpUjNs2DAVVYvpHmraIiACIpAOAYl06VBSGxEQAREQAREQAREQAREQAREoEYGpU6eauXPnWoGuUaNGJZqFhhUBERABESg0AYl0hSas/kVABERABERABERABERABERABERABERABEQgBQGJdDoiZUtg5MiRZuHCheaaa67RN4Zlu0uamAiIgAiIgAiIgAiIgAiIgAiIgAiIQD4ISKTLB0X1kXcCiHNdunSx/dbU1KiiYN4Jq0MREAEREAEREAEREAEREAEREAEREIFyIiCRrpx2Q3MJCPznP/8xffr0kUinMyECIiACIiACIiACIiACIiACIiACIlAVBCTSVcU2x2+REunit2eVPOP777/fXHzxxda78/bbb6/kpWptIlCHAJ7NJ554omnRooW57bbbREgEREAEREAEREAEREAERKBABCTSFQisus2NQJxFuu+//9489dRTpkmTJqZ169amefPmZuWVV84NiK4uKYFtttnGfPPNN3YOzzzzjNl4442LOp/ff//dTJkyxfzxxx+mffv2Zv311zcNGzYs6hw0WPUS8O/HTz75pGnXrl31wtDKRUAEREAEREAEREAERKCABCTSFRCuus6eQJxFOjxOpk2bVmvxW2yxhdlqq60M/91tt91M06ZNs4ejK4tOYKONNgrGnDx5stlyyy2LOodx48aZESNG1Bpzww03NJ06dbKi3U477WT/Kysuga+++sp6VvK53m+//cyKK65Y3AkUabQ434+LhEjDiIAIiIAIiIAIiIAIiEBeCEikywtGdZJvAnF+KNx3333Nu+++mxQJbYYOHWo97WTlT8AX6R5//HHToUOHok76iiuuMDfffHPSMbfeemszePBg07Vr16LOrZoHu/baa82YMWMsgssvv9wcccQRFYkjzvfjitwQLUoERKAqCfD7hvvxqFGjbJSGTAREQAREoDIJSKSrzH2N/ari/FB41FFHmRdffNHuwS677GK+++67hKLdZZddZo488sjY71clL+Cvv/4yLVu2DJb4r3/9y3pFFtNuvPFGc9VVV9khEXabNWsWnLHwPA455BBz5ZVXmhVWWKGYU6zKsdgT9gYbMGCAFUkr0eJ8P67E/dCaREAEqpOA+8Jw4MCBZtCgQdUJQasWAREQgSogIJGuCjY5jkuM80Phqaeeap544gmLfeLEiTYk8csvvzSPPPKIufPOO4PcZm5fSMS+9957x3GbqmLOf/75p2nVqlWw1kcffdTgtVZMGz9+vLngggvskOeee6455ZRTzE8//WTP2d13311HBD7hhBPMhRdeWMwpVuVYN910kxVEJdJV5fZr0SIgAiJQVAIS6YqKW4OJgAiIQMkISKQrGXoNnIwA1QSppInV1NSYzp07xwbY2WefbeeMPfDAA2bHHXcM5k4BgHvvvdcMHz681nooNLH55puntUY8u+rVq5dW20I1Koc55GNt3377rVm6dKkNG0nkeUaxBj8s2Qmv+Rg/3T4mTZpk+OYcw1sLry3fXnjhBfu+K27Be1dffbU59NBD0xqiUvaz2Ou45557AjGU8PUzzjgjLd5xaxTnL03ixlrzFQEREIFEBCTS6WyIgAiIQHUQkEhXHfscy1WSewOxDkGrUaNGsVnDJZdcYpPJR4l0bhHvv/++6devn/nss8/sS6effro566yzEq7xtddeM4899ph5++23zZtvvmnWXntts/vuuxu89tLNa4cg9fzzz9t8JoTg8vPixYutsHPdddeZPffcMynjXOeAgIIY+dxzz5mPPvrIzJs3z+7r9ttvb0VYBKWoxPu//vqrgSntEUJ22GGHYJ6ffPKJZeLWQT+77rpr0nXQDx5Qs2bNMosWLbJtV199dfOPf/zDhh7Xr1+/1vVhke6hhx6yc0bco0AIe8j4bdq0Md27dzcUdMi3TZ8+3eAdh0WJdLz+ww8/mDPPPNPuMdaxY0d7ZhJZrvtJv08//bStdst5huuqq65qx6WIBSypQusbLJnTzz//bPbff/+EFWrnz59vzwlFVtq2bZtwDfSD6P3GG2+Yt956y+4n45Mbrnfv3mkXcliwYIGB8dy5c+3ngs8He8rZIwch4cW+/fbbb+bzzz83iKd8djCE05NPPtmstNJK9l+phfR8nkGJdPmkqb5EQAREIDsCEumy46arREAERCBuBCTSxW3HNN+yJ0BCX/fgPmHChMAjMDzxmTNnBp5OVId0IbJ+u2XLltkEwU70i1o8ebH69OmTkMuHH35oLrroooQ5zLgQYYuwySjLxxwQ5RBbXa6+qHGYA9zWXHPNWm+TAw7xCaPgBjnAeO2f//yn+fjjj2u1RWx75513Ir3iEIjGjh1rLr300oSsEglgfuEIvCQRg5xnm98Z47OPfnhsPg7sSy+9FOQuTJaLZsmSJVbwJBQWQ8AM88zXflJt9t///nfC5cGCgheIcc4Q9I4//nj7I15niK5RhjjH3iJGIxCtvPLKdZq9/vrrdg+c0B1uwGcKTzf6SGQIc4SrfvDBBwnbnHfeeVZ8c/bLL79Y71jfazHRxTDAQ/b++++PXEM+zkYx+pBIVwzKGkMEREAEkhOQSKcTIgIiIALVQUAiXXXss1ZZRAJ+xcdklUDx3unWrZudGR5HPAiH7cQTT7TeWs4QshAsZsyYEQgxvHfDDTeY/fbbr8719Iko4kQbvwECgv86okhUyGeuc/jqq69qeb8l2wp4IKz4Rs4+J6zhwdagQYOk4hCeZFEi2bBhw+oIkXhdIWL6HKJCj32RjsIMeNMlsgMOOCAQafN17F5++WVz+OGH2+7INee86sL9461IDkQnIHFOwhXgct3P//73v/bchs9U+Dy5uSGaOk/YBx98MPAYRby7/vrrIxG1a9cu6D9qDfTZs2fP4FqEOMLjOcN+ZeVNNtnEPPnkk9azLWwItiNHjowc318L3pG+SP6///3PMs7EECc33njjTC4pq7a+SBe1H2U1WU1GBERABCqUgES6Ct1YLUsEREAEQgQk0ulIiECeCVxzzTWB+IAHVIsWLeqMgJiAJ5ILTcQTzlXvdI2fffZZc9xxxwXX3nfffWbnnXe2PxPaSEifEyQQKRByCDd0RkieLwwgPJx22mk2TBbxgnBNv0opnklNmjSpNddc50BneEz5YZdUv8Uzbr311rNeUIhOjgMiXFgAI7caImTYWDMhsptttlktr7aowg5wwgvP2cEHH2wFmoYNGxpCZv0QWUQsV6TBtfdFOn8eFJAgTBghdfbs2cFbCH9RwlC2R42cc0cffbS9HBH4oIMOqtPV999/b8N4b731VvtelPCbj/30C6MwDkUsTjrpJNO4cWMbHoqgetdddwXz8735OMN4pmFRZ95dtM022wRCY1g0xSOS9Tve7CtnhPONkTPQr3p38cUXm2OOOaYWL671PfwIUeZMEkrN//sef4STE3rrG0Iy3nd8vp0357bbbmuvZX78QzAlByWCI5+BOFfbxUOT9AMIvoTpy0RABERABIpPQCJd8ZlrRBEQAREoBQGJdKWgrjErmsBll10WCCUIUAhn5LjCu+mLL74wiGHhUDmX58yB4QG/a9euQShflNBA2CVFKpyRY2ydddYJfn711VcNXl/OCDUN50vr37+/9TTCELIQrfI5B98DjH7J+8aYvvlFERBfEKF8QzCjuqlv++yzj4EzwhCGUOZCFsMiHdVZ4QAfLCq0FzEUAQtD9EHs8s337OJ1BCGq9bpiH4iNu+yyS3AJnkfhfGy5HHpfNEKsI+cbohzniNxpeJaFQ3/PP/98K57lcz/DIl/UufQ9H9kjctM5Q7xzRVOOPfZYK1RHGSxdGGvYG9UPf0ao5Vw7gY6+li9fbvfY5RuMGgcPPsR0jM8E6/JFVT+kNVluP4Q95oMl8mbNZd91rQiIgAiIgAg4AhLpdBZEQAREoDoISKSrjn3WKotIICqsMtHwCDl4PiEE+IbA4CraIkDgjeSKKpCgH08e8t05ixIS/BA12uHNQ4jgpptuGhRHQOihAm2HDh3MTjvtlPc5+F5XeO/hFRUuDjFu3LhArMHTzxcemRCvTZ48OZgbghueU35ifgQpCggg2uDdtNpqqwXtKShACKoz8qi1bNmy1lrxpnOedoRB+hV5aeh7dvEzoiEiqm8ujxqvZVKtN52jOWXKFOuxlq4hQPkCLdfl40whyt1xxx12GniOIS6HC22QM9B5hYbncfPNN9s8dRghu4jYUeazDFfTdXvNdb5ISBEJBGdEXj9PHbkWw8VEyGc4evRoOzSfL4Rg2mywwQbBdBB92UfCyMPnxTXCK9TlWeQc77HHHulukdqJgAiIgAiIQEYEJNJlhEuNRUAERCC2BCTSxXbrNPFyJZBMpENM44EfDyxEuC233DKyAqVfKADx4Nxzz7V52PAq8nNuwQBhCiEjLCQQaof4FpU7jPxdjI/QhHgWZbnOAQ82kve78cNeVW5MxBJEEwyxhHBT3/r27RuEw9IfnnLhUFIEGkRJ1hsO2cXjjYIQGMISP0cZvBD+osISYeU8s/h/vBjDRkilK6RAeG9YeM3lvFKMAsEzygjHJKwZ8XW77bazlWd9kdJdk+t+0g958fCOTLRXvO4LYGGRzn8vKqzYzdX3jCSPnV/Rt1evXoFXJAIcXm9UmaVd2KJEX9qEw5/dda5qMuMhFIbPUrh/hF33eaQ4RFjozmXPdW31EKCKOQVMuP9QyTpO1cyrZ5e0UhEoPQG+RORvHTzSw/lmSz87zUAEREAERCBfBCTS5Yuk+hGB/0eAXGf8IRVleLIhRKUKhfTDApOBPf30062H1RprrBHZ7M0337QhpnjfJTJEnSFDhgSee65drnOgwACimDOELecd6M/l8ssvN7fccot9iQdUl3vNtfFFGUIp995774zOGp5beHBhyby3knXqe9LxMH3YYYfVae7n3nv44YetYJYvmzp1aq3QVb9fhEu4kR8vmeW6n/Tth/2GxTM3tl/dGAGW/XPmi3TkNkPQjrK///3vwZn1KyQj/KZTORcm9O2Le+Fx8ALk7CWr0ooH5llnnRWZV5L+fI+/qFyI+dp/9VO5BMjjyD3NhatT8Zh7STUYXy5R+Zt7BF82yERABERABERABERABIyRSKdTULYEELvwMMAbJ06eBX5OOoQpRAvyw/lGuCZFDxKZ710WboPARw613r17Wy+6dGzOnDk2DJTQPBeeF76OPGx+cYVc58BDJyKGs5kzZ5qmTZvWme5FF11k7rzzTvs6ogkFMXzzBRvyf/nFLtJZO2IQnlYYye8pGpGp+eJUOPzS9eWLdH6Rj0zHimrv56Tj7JBfL+zNxzoRZBMVrMh1P8NVTRMVRfFF0TBv8rYxfwzPQ8JVo8z3UPPDVZctW2batm2bECliB58NxGA/HDrRBXhPci6pWIoXZNhLlev4jME6yuPUz52X7xDnfJwb9VH+BPwQcGYbriZc/ivIbob+Z5mQc35HpfOZzW40XSUCIiACIiACIiAC8SEgkS4+e1VVM0WcIyQTS+SBVa5A8LRyhQdeeeUV6zVHmGrYO4J8Vnj7rLLKKnWWQugcIa7OeIihGuWBBx5oPbRyqRRJeCBiBHnOGMeFo5JA3xfwcp1DOBdcuLAFa6MKJqGNzouEfHSEKPrmeytl46HmX0/+P0S/TM2v7ppIjPHz7+FJybryZVS/JewXu+6662yOPYpFULjALxiB5yJnj8q5Yct1P7/++msbSuuMEFw81sLm560LV6K9/fbbrdcfhlcp+euizBfpwizDRTyYA5Vie/TokTI8NdV+UDWZc4oQ6+dBRDhGQA6bHwZN8Yk2bdqkGkLvi0BAIPyZ4g1E4TfeeKPiKfF7h8+ys/nz55sGDRpU/Lq1QBEQAREQAREQARFIRUAiXSpCer8kBPyiB3ET6fAUwmMIQwijEieGmIK3ky+q8JBPGGL44eSFF14Iwj4R6Hhoo0pslOEJRAGIvfbaq1YS/w8//NBWksXbx0+I7/dByB/hVc5Ilr/yyivbH3Odgy+00l9UsQW/sittosJR/fxkUUUAUh1QCig4T0bCehG2ouy9996za0bUI8ebM7ytfPEFr7woryoqqRKWiuW70qcv0uFh6gS7pUuX2lBlNy5jJ8pRmOt+hkNNEZg5z2Hzq/E6QdG18YXCRLn9qIRM9V6XA5BCFZxtZ4jVs2fPtj+Sl+f444+P3E8+E88995wt+uGLrDRGPOd8UhQi0ecKrojCWKK5+gIwAiReUDIRSJdAotQI3O/T9ZJOd6xyaxe+n0ikK7cd0nxEQAREQAREQARKRUAiXanIa9ykBOIs0vnhfmFhCu8BRCIXfgkEks0T7umLBV9++WWtCqNRIZY85BDCeP3111uWfqgohRQoToHhyUeYaNi76ttvv7VFGvAcwnbfffcg7JSfc53DX3/9ZQVK56mH9xeijTPESryp/MIWCHLhfH54SXEeMNaKSJOJ+eG0eAtSATScww+PFgQX5oIoigjkwkZ//PHHQGhlXISfqPxJhFniTYVFVVfNZM7htvRL/xh5CMmT5gzOcCGs2hkP+ORIY73Oct1P+vELRyBU4k0X9gTFG9KF4ob3K5xbz38wJzcXRT3wxPPPRFik80VABGiq+oaNPFdHHnmkFfpggZDt9nPWrFk2VByjKAvnLVxxmByO5Mly84gqaML1/fv3t+cp6vOTy36X27UImtwrWrRoYcgLKcudgP95JASfc4rQi/l5GHMfKb0euI8UO9zUF8/5zIY/h+nNvDSt+BIAr2DCdqk4neiLsNLMTqOKgAiIgAiIgAjEmYBEujjvXgXPPc4iHX+wO+EgSqz57bffzMCBA2uF00Ul0R80aJANu8MQ3AgNxKOLEFGEBpLwu0qbtPGrpyLA+YUE8EzCu4uHIDyVCL8lFNFPmh8VCprLHJiT71XIz7BBrMOz7ZxzzqlTeTYq1MvP9YaAQy6zTCwcdkvIJiG1nTp1MhS3QJC58MILAxbMAQ9E98C6ePHiWkUgEuVi86u7ZjPPZGuiWqwLl0Zg8gU5d124MARhoIiz/oNvrvvpfy4ZF3HhvPPOM+uss46dxoIFC6xnnxN+w3kOw+F9zBEvtblz59Y6yz6LsEgXznXI3lFsBLGQ84z3G58FZ+wn581xmDZtWq0KwlyPByf2ySefWIHRFRpxfXB9VAhxOJ8Y80BU5vOKQEiuO1jg+Ugl57iav++Ikn6YYlzXVOp5+150hNDjxew+4+SWRABOZXwZw9nkc8fnYsmSJdYTGvGLkPFwxe9wf5xN7i1vv/22ociQq25M6H6iQg6Mdemllxq+JOI+hzjF55q+OCekUyBv6EEHHZQwfJV7KgI4Irkz5sDcEdNLIdaxrunTp9t7Eb8/+T3JPPnygN+XzZo1q4XPL5DDF3PdunWzeS3xyGZf4Ef+TF5PR/xcvny5eeCBB6zX/Pvvv29/L/FFCPdHvrzyWTER5sWe8TeBX4UasZX7DvtDyhA/Ncann35q5+a+wHP37Fz30wfDuHzJxRdLjAdL8pnCkqI/eO/Xr18/1dHW+yIgAiIgAiJQ1QQk0lX19pfv4uMs0iEAuXxWiR62CKFEMOEByRnFAfwwS8JV99hjj1qbhJeX72Xk3kR4QqThfWd+WCCvJbqW9xAJ8RYK//Gc6xzB3+ezAAAgAElEQVQIx+QhJVkFTR5AfM9CHjwaN24crMMvxIG4CbdMDe9FBKt0LJxHLSwKhefn+vS9zBCuTj755HSGS6sNhSjoE4PnPffcE3kdryM6OQtXos11P+nXz73nxsFbk4fG8D5TtReB2Ldk1Y9pR18u1JWfwyIdr+FJSHVZ3xKd7/AcmCMhsOlcS5tkocvksKNYhT/fqI1Jln8vrQNQ4kZxvh+XGF3k8P4ZdJ9n/z7DmUrmscjvD77AQRxKdm9FLPnb3/5WZw54fyEyOc+9qEleddVVVnAOmx8Gzu8MPOAIYw8b+TFJTxD2Wg7foxLtD59nvMtHjBhhw9ILZQhz3CcRSRNZ1P3c/8IDcTPRPhACzz4lC18mnQH37c8++yzhHPCgHjx4cCC6ufQKeEvzt4NLU8HvOZfSAXbHHnus7fPzzz83O++8s/1/PPfxnMdy3U83YcQ5vrTAMznZmVQV7EKdZPUrAiIgAiJQSQQk0lXSblbQWuL8UMgf205E8b10wtuDxwHeVy6Uk2/hw54PFHigTbI/ehGH8GgIV/VETCLkL0rUc3PhQWjAgAFJBaVc5sA4eCgQqunn4nPjM3cY+Z454Qquft46BFDCKTM1HkrJoRYWdvx+YMHDVDic1vf+og0eH1GeHn7BhKj8e5nO2W9PWCniGBYVEuy35eHaFWQIC460y3U/EQgoaoJHRCqLKqDBued65yXq98FZPOWUU+xDJh5vWFSoN3MgvBsBL5GxV4ibvkepa0s4IQJ6MuPhlz0Ne7CEr8Hjhb2JOt+ubZRYmYpdOb0f5/txOXF0c6HqMZ9NbNy4cfbLGDyknfdasuIRiCHcTxF2UhkC1KabblqnGaHL7vPFm5xxRB48sPzfF1ECtZ9+INX4UWHifvqBVNfzfjhNQjrXpNuG+xNfGkSZL/pHVdz1c5CmGi+Z6MoXVFG5PaP65L7J/RHzq57zZV/Hjh3t6341c1JpOAHV9yD2vzzMdT8Zk3s6X5xEfREW/vIkWR7RVBz1/v9VqOd+jMjevHlzIREBERABEahQAhLpKnRj476sOD8UEtqBsIQHQ7LE9OwRoa+E5/FwtsMOO0RuG+EiPJARtkkoDd4FeJoh6PFw5f44j7r4q6++MoRSERLlHuoIOeFaPDjw8FlttdVSHpdc5kDnhGEhNFE9llAe5kClWrys8N4jdxmhwTyc8jDhh+8gsBE2ycMjXgF+nrWUEw81oHgCIcKEC7Omdddd1/6hi4cBD8qNGjWK7JK5EwaFgLfZZptFtiFHEZ4j7A3iYz5DtvBSwwOB/HiEsUWFXvqTgiHcmG9UqFWu+0lIFXvJQz3hv4RQNWzY0J4r/0EtWaEPzjK54iiaQigoXqSOGWcEgY118lCaKFyMc02YHZ8NvNo4P/DHi4ccg2uuuWbCIzJnzhzrgUIfrIVrOZf843NBvrt0qyjzOeZBGWEcjxwEc+ZBTkbmESWUZHp2S9k+zvfjUnKLGpvPCueT+1k4FNv3xuWz0bRp0zpdIOrhIeWM+wGiHZ8f+iZcEq8rDDEOocw3P78lr/M5cx5WfIaoZIyQjzE/7pd+vlRfHHL90o6QbsIz+d3nBMBwxXDaI2aTDoJ7EG2dEcaPUOn+IUZyb6BfwmfzbXgZ+l/IMFe+HOD3sPNOc0Vp+P1MLlLffDGM17kG4Q4vXebN7zN+bziLKjjEPZr7g++JyxcDpBGAOXPEe9x52OFJxxcZmO+xj9clQiDsuJc6oRWBjN9bmO/B6Bf0yXU/6duv2s3PiIPwgQX3Qd8bnrOKUCvLjoDL45htVEF2o+oqERABERCBYhOQSFds4hovLQJ6KEwLU0U1Qsgjr1i4EEFFLbIKFoNo4B7yS5EAvwoQF32Juh/nD7lf4dgXXRjB94KN8kIlZ6Lv2elXenYzRGjr0KGD/RHRD+9gZ4jrXbt2DUSfqNyZ5GT0vZURwV3OSfohR5ovKhE2iVegE8TJ84kI6SxR1VY/9D5KzMsf8eie3BdDvMv4iJe+NzreYTvuuKP1YueLMD81Bdf4Ih05LfEk88VMvH1JQ+G84PmCyRdX6QNueEY5i/Ia9gvx+CHIvjem804Lp2agX1cp2C9o5Yec5mM/fXEZzzzm6RtfiPTo0cO+hNcx+Whl2RGQSJcdN10lAiIgAnEjIJEubjtWJfOlmiBJjzEeGvhDUiYCIlD+BPAMcaGfhMTyoCqLNwGJdPnZP7zD8Nh1nw9EOnK24X2NlyyCihO4w1WcmYEfph0VgkkbCh44z7NDDz3UFu9xhrjmfpeGQ/cJ28bbijGcRYlTfkVWCr/gCY7nmG94UDlxCvGL4gZhozgPHmMYhQzw+C6mUXiJ6ugYLPA4RAD1q7TiFcu88IgPp6LwRTqqUvvCpFuHPwasfM86zgKvOa83PAajQm/90GTfMxmhzXnVOQHQT4vg5sD+bLfddrVyicLeeavnYz8POeQQ65GM4U2JYMk58z2Z8WLnbHMmfU/5Yu55JYwlka4SdlFrEAEREIHUBCTSpWakFiUiwLfOiHXk3kgUhliiqWlYERCBBAT8B3Q/V5KAxZeARLrc9w7xbOjQobWK5CTrFdEH8cc3v3J4ooImflGKcCVoQtPJU4ohSJHjjFyoVC914qAbjxBWPLt8cQphiXBwZxRIiqpa7BctomIpHmlh88Nuo9aaO/HkPbBevH7D5ircEvbKFw6JBCVfpEv0RWJYNKPaqTPC/RFanSXKH9irV6+gWrafr9WvWu6KjzhPTDwDXYisq/ruPJz9ENh87Wc4BNutCcGOufFFDR6cYTG30Htcif1LpKvEXdWaREAERKAuAYl0OhUiIAIiIAJ5I0AREOcdQh5E/6E+b4Ooo6ISkEiXO26KyYTzw6Xq1eUgde38UHL2hErIYVu8eLH1nMLwVPPDKakATmhkKsOLj1yQ4cqs5LzD680ZlV2jcm/63l+ElYaL8XA9HmquAjaCIV5ixTY8fSlAk6wwE4Ur8Axr0aJFren5Il2isH5yVJJ71Rkhvi6k9sknnzT9+/cP3sNrz1Vo9Qfy93zq1Kmmbdu29m3fY9IVGqHIFKIrXG+99VbbjtcIa3b3ZTzcEBWxfO3n8uXLbegu1V0TGeIgc8H7T2Jd9iddIl327HSlCIiACMSJgES6OO2W5ioCIiACZUzAr1DJNP2wqjKetqaWgoAv0lEsRFUFMz8yYc8tPMWbNWtmi6PgrbXWWmsFhRJckZ9wGKUfmhgW8NyMKBbkihCFK6MS3kkIZpQh+JHUH+87RJ8o8730eN/3DPPbUz3Uhc1GVXilLV62Z5xxhr0MIYriQKUwcsdRpINzjcAV9ihkTvBA2MIzzJkvRCaq5v3OO+/YIjTOqAzuQkD93H+wd1Xewwz89AHh4hP+FyIUiECc5QsSWCKOEsJMdWs83VyVaz83Xj73k3mTV9YVE6Ioj5+70K0Lr0nCqhHtZJkTkEiXOTNdIQIiIAJxJCCRLo67pjmLgAiIQBkS4AGRB0dnVGlVIZAy3KgMp8TDN6IS4tygQYMyvFrNIYBnE6GHGMLNjTfeGAmGypukeMDOO++8wNuMn/0k/64gQLgThBkqdmJ4sCHWOPOLVvAaQglt8PZC4ElVzdgXALmeQhZU5w4blU3duHh1sY6wEbpJNVUsLCaW8sRQeINiGYT6Es7rjKq3eN0580W6O++801BAI2zhSrq+56FfETWqeix9ffHFF7ZSqrOwaEuFT1chlzkgsmKIvFdeeaXBWw8jf53z6POLT+RzP6P27Msvv7SiHSHPMHXmV5ct5V7HcWyJdHHcNc1ZBERABDInIJEuc2a6QgREQAREIIIA1SPJP4UHRTk9eGuzRKCUBMj9RW4ulyfstttuM3vvvXfklEiwf/TRR9v3dtllF3PvvfcG7fz8ZPfdd5/Zeeed6/ThVy096KCDbBiiM79vBDqEPr8iqd8Z3mXff/+92WuvvQIhjgIXnTp1CprhddawYcM6c/BzlCXykvPDPUtROOKVV16xOW8pCpGIwZAhQ2xhDMwPE+Xnk046yRB+iiXaz0suucQgxmF44eEJ5wxxDZHNGV534dy7fmXXqHEI1yXPIUZoM8Ii+0o1VbwmEcMwBEU3jylTppj27dvb1/Oxn3gispd8GePn2PMPBecfDzoXVgxXJ9CW8nMZx7El0sVx1zRnERABEcicgES6zJnpChEQAREQgQQEeBAjFI9k4VH5qgROBKqNQDg3WaJQVbggjFFV1RlhjC40EGEDDzQMIQ8RyDdynlE91hlVN/Fqc4Znk1/EAVHHF91oh6CCwOM84fAew4sMW7ZsWZATjZ8RuvxqqG4cv2BCWJxybXyPP17ziyIU+nzMmjXLhvVi5MMbO3ZsnXsV80MUdfk1w2G75JNznmqEl4aLUOCRR6iqE6YQyvychOH1X3HFFebwww8Plu6HA7sXhw0bZsiF5+zzzz+vI9S6L0eiruc6Py9ePvYTj1C88zBExdNOO63O9vmVaIu914U+S8XuXyJdsYlrPBEQAREoDQGJdKXhrlFFQAREQAREQASqgIAf/hkWzqKWT7gqIg7mhwbiuYUHlzMKAhDGSDgy+dTCYaWIPog/vhGujDiH4cGGyNKmTRtDPknEK3LWvfzyy8Elrjqoe8HPi+d7ZfljENqIwOUsKnfdb7/9ZjbeeOOgDSGfCF9O7MKzjDURgkvhhnzatGnTrHeZswsvvNCccMIJ9kdCeMkXFy6C8Oqrr9r8gc5OPfVUgxgZ3iN+RgwlL5/LLchrYUETr2M8HRFwnVE8Y9NNN7X7c/XVV9dZctTZwdvSeWhygRP7SDWAF6RvfHGC951vue4nZ/COO+4IunRiK2Ivnpp4VTpONEok2uZzfyu5LwrBkL+QkHjlBq3kndbaREAEqp2ARLpqPwFavwiIgAiIgAiIQMEI4F3k8pshxOC9lczwTHI56/xcaIQWIrQkq0bq90uOsosuuqjWUGFvO97EU895jIVFHSrC+kn+fVEoUcgtohHtnCWqXJputVlEtc022yxv+xMumJCMAe/dcMMNNizWN4pe4K3mDMGT6qxUTGW9vuEBSYhn2MIellEL5Kw4sS9K4MK7zq+MS8EGxE9EQLwk/bNyzjnnGMRF33LdT+bWt2/fWn0mOk8U4CAvYj73Mm+HQh2JgAiIgAiIQBkRkEhXRpuhqdQmMHLkSJszBi+EcK4WsRIBERABERCBOBBAzMLLDcEFYapevXpJp02oJDnryO2Il5LvEUUeuGOOOSahUEcBAwoWYAMGDDCDBw+uM1aqPrgALzy8pFZaaaVa1/ueeHhlIRqGDYGIeXz88ce2MiqedVEFJmiH59ctt9ySkMcWW2xhQ2HzHTpP9Vm83ZLZhhtuaBlEiao+h2R90M7PPRduGyVyuTbkE2zatKk57LDDgsvCXom+d6XLR+fOV1jAe+qpp6z3pG+57id7SB+ugEUiFuSkw/urZcuWcfjIao4iIAIiIAIiUFICEulKil+DJyKAONelSxf7NqEnJG2WiYAIiIAIiEAcCSC4NWnSpI7olWgt5AvDu41rwkY4JaLI7NmzrdcWHlZbbrmlrQT67bffBqGb4Txqfj+0QyB66623bA5Jiic0btzYiiiIUn5ePP+6BQsWmPHjx5tWrVqZI488MqHgSPECwjbJyxZV4MLvk9BM8rshHhK6u8YaaxjCMLfaaitbqRYPtUIYc8TzjFDWF1980QqKrIt/VODFyyxRxVtCcB988EE7LXcdTPF2RCyjUMiee+5pq+amMoQ31k9473fffWeFtGOPPdbuASIY3pSEIIeLV9Av45Gnjr1EUETAdQZLqrxyXnr06GEIlw1bvvYTYZg5EtbLPiJwsod4zZH/LywOpmKi90VABERABESgmglIpKvm3S/jtZNzo0+fPnaGEunKeKM0NREQAREQgbIhQH61e+65x84nWRXZsplwTCeCFx7eeFi4oEMhlkTY6lprrRXpkch45ICL8lYsxFzUpwiIgAiIgAiIQGEJSKQrLF/1niUBiXRZgtNlIiACFU8AzyPyjeFpQ/L5cIL4fAPAs5lE+y1atLDCj6w8CeB5h+eWyy9H8QWliijMXvmhpOeff36tgh6FGVG9ioAIiIAIiIAIVAsBiXTVstMxW6dEuphtmKYrAiJQNAL+/ZFBCVNErOMfYY/5Nn88wvLatWuX7yHUX44E/LBHuooKjcxxCF3uEfCrmkYVZBAsERABERABERABEciWgES6bMnpuoISkEhXULzqXAREIOYEPvroIzN9+nRD5cvXX389WA0CGmLdvvvua5o1a5aXVep+nBeMOXdCyCMVQcnX2qBBg6A/csohGpFXzdmtt95q87nJCkOAghc333yz7Xzo0KGGaq8yERABERABERABEcgHAYl0+aCoPvJOQA+FeUeqDkVABCqUwKxZs6xYh2j3ySefBKskaf+BBx5ounfvblZbbbWsV6/7cdbo8nohRQEoLkBhgn322cesueaaZt68eTZhv2+nnnqqwbtLVjgCVF4dM2aMHYAKulTSlYlAoQmMHTvWzJw50+ZBbN68eaGHU/8iIAIiIAIlIiCRrkTgNWxyAnoo1AkRAREQgcwJPPXUU4GHHdUdMSp34l2HsEPVyUxN9+NMiRWmPcWU2Itk1rdvX/sAv+KKKxZmEurVErjlllvM5Zdfbv9/4MCBZtCgQSIjAgUnQMVcnbmCY9YAIiACIlByAhLpSr4FmkAUAT0U6lyIgAiIQPYEli1bZiZNmmQ97J577rmgo5YtW5r999/fFpvo0KFDWgPofpwWpoI3ItyVEMuJEyca/t8ZnnV4TSIWbbLJJgWfhwYw5q233jIHHHCARaHQYp2IYhGQSFcs0hpHBERABEpLQCJdaflr9AQEqCZI3h2spqbGJsGWiYAIiIAIZE7gyy+/tILd1KlTzezZs4MOuK/uvffeVrCjcmsik0iXOfNCX4FIt3jxYtO0aVOz1lprFXo49R9BgOq5y5cvN9tuu62pV6+eGIlAwQlIpCs4Yg0gAiIgAmVBQCJdWWyDJhFFYMSIEQaxbtSoUaZRo0aCJAIiIAIikCOBOXPmmEcffdRQpfXzzz8PeuvRo4cV6/jXsGHDWqNIpMsRui4XAREQgTwQkEiXB4jqQgREQARiQEAiXQw2qZqn+NNPPxm+rZaJgAiIgAjkl8C7775rK4IiwuERhOGV1bZtW9O+fXtz4YUX2tck0uWXu3oTAREQgWwISKTLhpquEQEREIH4EZBIF789q6oZP/zww2bIkCFVtWYtVgREQATKgcCJJ55oLrjggloi3YwZM1RVsBw2R3MQARGoOgIS6apuy7VgERCBKiUgka5KNz4uy3722WdtUmaZCIiACIhAfgn89ddf5n//+5/998MPPwSdr7zyyqZx48bmscceM+utt56hSizpB5o3b64qlvndAvUmAiIgAmkTkEiXNio1FAEREIFYE5BIF+vt0+RFQAREQAREIDMCzzzzjM1LRyGJX375xV7cpEkTs88++5ju3bubrl27ZtahWouACIiACBScgES6giPWACIgAiJQFgQk0pXFNmgSIiACIiACIlA4Am+88YYV5qZNm2YWLVoUDOSEOcS5NdZYo3ATUM8iIAIiIAI5EZBIlxM+XSwCIiACsSEgkS42W6WJioAIiIAIiED6BD7++GMbsoowR1VXZx07djQ9e/a0XnMtW7ZMv0O1FAEREAERKBmBMWPG2Byho0aNUm7Qku2CBhYBERCBwhOQSFd4xhpBBERABERABIpC4LvvvjOPP/64mT59unnhhReCMckx17t3b7P33nubbbfdtihzieMgP//8s4Fhs2bN4jh9zVkEREAEREAEREAERCDmBCTSxXwDK3n6I0eONAsXLjTXXHONadSoUSUvVWsTAREQgawJUABiypQp1mMOce6nn34K+iKc9cADD7Rec/Xr1896jFJf+Ouvv5qvv/7arL/++mbFFVesM51vvvnGLFu2zBa6WGmlldKe7rx58wweh/TfoEEDc9555xn6Gjp0qDnjjDOCfv7880/7uiuy8eOPP9p8fmuvvbbZcMMN7bgrrLBC2uPmo+EXX3xh3n33XbNgwQLz0Ucf2fmtttpqZt111zWExXXr1s3+VyYCIiACIiACIiACIhAfAhLp4rNXVTVTxLkuXbrYNdfU1JjOnTtX1fq1WBEQARFIReCVV16xohzi3Oeffx4032KLLcwhhxxievToYQWbuBtVvo877ji7jNatW5vJkyeb1VdfPVjWoEGDzMSJE+3PvE44WKovdp5//nlz9dVXW5EryhAD6Qej3Q033JAUI+Oee+655rDDDjNUxy2kIVZef/31Zvz48SmHee2118w666yTsp0aiIAIiIAIiIAIiIAIlAcBiXTlsQ+aRYgAD0d9+vSxr0qk0/EQAREQgf+fwAcffGA9vd56663gxTXXXNMKc7169TLt2rWrKFy77bab9XZzduutt5q///3v9selS5caREnfkv3O+P33363odsstt6RkhHca1qZNm5RtXYPNN9/cTJo0yXrlFcLefPNN6xkZNkRChMklS5bU8qSkgm/btm0LMRX1KQIiIAIiIAIiIAIiUAACEukKAFVd5k5AIl3uDNWDCIhAZRLw74/kmCPXHOGshTI8m0888UTTokULc9tttxVqmMh+o0Q4wlARKTG8CfFe8+26664zBxxwQGR/559/vrn33nuD9zbZZBNzyimn2Mq248aNC7znaEAoLOGjxxxzjPn3v/9tr+HLo+22286Q469evXrmhx9+ME8++aRBDHNGm6uuuirvnP773//anIKEtWJ4FZ566qlWsGzYsGEwHiG58+fPtz/vvPPOeZ+HOhQBERABERABERABESgcAYl0hWOrnnMgIJEuB3i6VAREoOIJcI/EYy5VWGc+QPj3YwSpYnrqIZQ5rzm3FgTJ22+/3f7Ify+55JJayxwxYoQ59thj6yz9jjvuMBdffHHwOkLe6NGjgxx3eM7tvvvuwft4LBK6SqgtIbfYfffdFyl8PfXUU+bkk08Orp0xY0beqy8yd9aAUfzjzjvvLMr+5+MMqQ8REAEREAEREAEREIH0CEikS4+TWhWZgES6IgPXcCIgAiKQgEAp78fPPPOMOf7442vNjEINL774on3N5aOjgIPzMBswYIAZPHhwrWuo2LrVVlsFr+GRdtNNN9UqQkExiO23396Gix500EHm2muvte0PP/xw8/LLL9v/f/DBB80OO+wQSerMM880//rXv+x7fkhuvg7WvvvuG+TQQ6zba6+98tW1ofgInoFxtzitgyrMDz30kPWOPPLII8sKPVWO8SLNxSjksmjRIlspeZVVVsmqqzjtZ1YL1EUiIAIiIAIiEEFAIp2ORVkSKOVDYVkC0aREQAREoEQESnk/vueee8yFF15YZ+V4vVHlFS87vO0QOlzIad++fQ3VwX3ziz907NjRPPzww5EFHgjtffvtt234sKsie9RRRwWi4KOPPmq23nrryJ3Ay47qsBiC3ZAhQ/K2Y+TS83PjkVOPyr25GEUlHnvsMbtect0hdOJJSAgtobSJ7O6777bXkRvv6KOPDpohktInhS34R8VbQoV9Yx14JfIe+5DMEEth2r59+6CQVLg9Ig7C6EsvvWRzNOL9yNwRNE844QTzt7/9LXIIqvnigcnZIXTaF14/+eQTy2Tx4sVW+KVw1a677poL6jrXsjbnkUo+wXfeeceeMf5Ltd4mTZrY/e7atatp2rRpwrE//fRTc+WVV9pKw5deemnQ9o8//rBr+PDDD+06EKkRAlu1ahXZF9WLEaDxAJ01a5YV1zgP7BF77HuYJgMBr3/+85/m1VdftWyd8Zk855xzahV8ieoHcZBw9DfeeMPuJ/NgDkcccYQN64+q7BzVDwwpqjN37lzz7bff2vXDgX1HHEU4TGbLly+3wvwLL7wQnAPW9uWXX9ozTZGYUtjYsWPNzJkzzbBhw/LuqVuK9WhMERABERCBaAIS6XQyypJAKR8KyxKIJiUCIiACJSJQyvvxqFGjDDnmsF122SUQy8hFR+VaJ1zhPYc4gPXs2dPceOONAS1ytHXq1Cn4OVHIaiK8fk66J554ok6hCncdIsdZZ51lf/zHP/5h+vfvn9cdQyxCtMAQUHhgTyQYJhsYDye4upDhqLbk1HPFm/z3ESl23HFH+xLi0pw5c6yYQnvnbei3JwyYYhrOLrjggqAqLUIp+f0SGbkHEQMxRBvWHJ4LYonLFxjuh/ndf//9kWIgwh5CKoagx3nhNc6QX6TErRPxbIUVVsjbfjIGBVGcwcgXtdzrrAGBmTlGGedswoQJ9i3CoSkeQ95IPDkRAn2jD7xHw0ZeRTxPn3766YTrI3ycfI7JKhdTMZl+nEdruDM+v3fddVdCoe311183AwcONJ999lnkPCgQg2gfPgd+Y4Q5REvE2kSGkO6HpvvtyIFJuDwejsnMhcLn7UCk2dFGG21kW8IJL2KZCIiACIhAZRKQSFeZ+xr7VZXyoTD28LQAERABEcgjgVLejxFhEFoQKwg7dTnZEMTwhunSpYtdKaGpPLhiiAF+cQg8ppwghaiFN1wm5uekC4tOfj+XXXaZFUcwilDssccemQyTsi3ec5dffnmtdggXCDyEABPOi9cRlX6TGUVApk2bFjTBSwzxBS8qX9i54YYbzH777Verq3B12dNOO62WIBoeF4Hp0EMPDV72Q3bDYqp/7VdffVXLuw0B0Pd+Yp7ssy8I4VmI4BQWCxHxWrZsWWtqCFl4nmGEOFONN5HYRxsEqEReaCk3LqJBVK7FZP1MmTLFehSGDQ815obBmc9qIpELcQux0zc87tgTXyBkX9ZZZx3rneiLXYlyPdIf4jUemL5xLr///vtAWOY9Pou+96VrjwjKuM6YK59txMx33303eJ1CL+TFXGmlleqwQLQOe9C6Rtw/3Nn2c1sCWnoAACAASURBVFr6nTgvuSiBzw+nd+sNV5XO5hxkeo1EukyJqb0IiIAIxJOARLp47lvFz5qQI/fwVVNTY8NNZCIgAiIgAsUnUEqRzglkhDD269fPevNgY8aMsaKNE4AmTpxoDj74YPse4gBiGhYOEyVUM9PQxZNOOikIpcXbCKEgbIgdeIU50ShKGMp151gL3l8IIskMDhdddFGkWEeoKUyd+V6FCFyEFTpRBGECwWvVVVcN2hP+FyWy0AARld/VeOk5oSjsUegLplxDSGaUqOiLaOuvv76t4uvnzLviiivMzTffbOfFfiDeOiEOwalXr16BKBPlQeaHP/ssWTNnarPNNgtEX95PFuaczb6y7rAACvs999zTjs37hOE6YYkiJ86j1B9v//33N7Nnz64zBT4D9E8YrPMwpRGhvPXr1w/a46mIx6IzP+ci52348OGB4I3QRSgs//UtLJgiXl1//fU27BivzR49egTeif5n0/XBZ4cckG4d7Bf748bhs+17jeExGA6j5lpYOEO05rNCGDP/7+e2ZF7PPfdcHWa+GM+bhLnTZ4cOHayI60Lrea8QOSfTOUcS6dKhpDYiIAIiEH8CEuniv4cVuwIewhDr+COxGBUMKxakFiYCIiACORAopUjnPK+oZkqON4QgDAGjefPmgZCCmEQhBQQD32Mo7KGDZ06mYYt4i02ePNmOy8N9OF/bb7/9Zs4++2yDmIB169bNhuUVwsjBhlcVQh0eVOGQRjcmDAiDbNu2bTANriXHmRPQosQOvhRjLc7IMYdXlTPyeZ1++um1loZIhijjwlr9KrTh0EJypPkehmFPOzpmnuRAc2GnhFASzuyM+eNF5yzsZcb1iDqTJk2yTaJEGT/s1vWDJx7ekI0bN7YvIZg5r6pCinTsFZV6wzn68CD1c5+R541cfr7BIew5By/OLPnbyMfmh0T75588dJxVdz05/ML5H8nNts022wTnDO9DxCvfrrnmGrv/GMIagqovvPoVmHmfPHG++aHHsCA3ny8EMgeEdRfqTegtXn2+MT7zwBDlEKN9bzvESsK0EdHh7MKoXR+Iif5nhb8/nejv2vj5MbMR+/NxP5BIlw+K6kMEREAEyp+ARLry3yPNUAREQAREQARKRqCUIp3Lw0aIGg/mLh8aXkeIL3hmYe+//74VVZzgQEJ9jLBT90CPh08qL7QoyK6CLO8hDiJsIELwYM+4PLAjZjlDIPCLPBRy4xAd8BxDPHShwG48hE3yvjkPNEQO55WOCIK3lkvETx+IEC6/GX1EiRl+cQzaINAhhjVs2DBYpu+dFZXDzy/EQahpOP9XOKQ2HOrq90/BELzuMDyyCNnFw84PeUWw8oVH2vrCKz+Tyw3B0PfWw2uTsGmEI0I/c6126p8D35MuHJ7t2lFEwc/nFyUMUXzCF2oRqliLM4Q4RFHEuXCYZzikGCF6yy23rHNcCSEllBTD2wwvTWdhT1XCzvGK843PCfkN8XZDHCXc2jfHmdd84Zj1E9pKn74QGcUBb8HRo0fbbjnbjIOwt8EGGwRDIbjiYYuHYTj8Ocyac8U8+Qy4PHywRMRGlOf+k24Ri3x+/iXS5ZOm+hIBERCB8iUgka5890YzEwEREAEREIGSE/BFOkQQPNiKZe6hFOGB4gQuLxhCGQIGedqcd44fjoa3Dq8jKOClhNGH87bJZP4UgyAMMB1LVHAhnWtzbYMIh+caIqEzvLF22mkn+yNCExU+MQQMV3QB7zg/7xfvI0zhGRgWMwjzw9vMGV5TvhDC64gZVKCkj0033bTOssiH5ws1zKtFixZBO5eHkBeiwjwRY1wIJ6IpYcaIlHhkOW8r1xlrZ//9kF3e83O5Id7iKRfOc4Zww9kn3JFqq/k0X6RDOEX8iTLfUy4qJ5z7fHBtWEBz/VFplwIfsPA5ELpKxVRnrmJyeB6+JxxCuBPsaIcYjnemM8TeKDETAZVzEZVLjtBkJ3IjwOH1Rlh51GcuSnBlbM5vVHENV7GYsFcKdSTbx3CuRrcmhOSdd97ZCtycNT9cOJ9nIp2+JNKlQ0ltREAERCD+BCTSxX8PtQIREAEREAERKBiBJUuW2BxwiHPkhSuW/fjjj0GyfBeK58JfCWnDUwwhCW8uHurx1kFUwZx4RF4qxBssWVXHZGvyPX0StcOrj0ILUcn9i8WLcdgrBDiXGw8vKAQpjMqapI9IZYSznnLKKWaNNdao0xSvJs4CFhUemapv3sf7CuHDzdEPZw17d0V54iUSU/yxEWfIh0fIYlR4sy8M4YmH51QxzQ/D5hw/8sgjkcP7YmI47BcxyxdBoyrgJluTn+uNzxNhplGGp6QryhL2RiXk2p0v9znMhCPCXToFORh32LBhtYqJhMfBI5PCKomqy9Ie0RfR3ReFXT+cPcaYOnVqwiXAiQIZLuw+k7Xmo61EunxQVB8iIAIiUP4EJNKV/x5phiIgAiIgAiJQdQQWLFhgQ0sxHqwRj/CccuGReLYgypG/DG8pHp5dOKvLU+aHViJQHX/88Rlz5DoELgxhigdlvKwQfxAuERD4rx8qmfEgebyA3H2EuWKIbS6vme+BFh6O4gx4YuFZhcCVyPzCD1Ghi+kug5BUij9geDwS4rrKKqtYLz1XIRexEc+qsPkCW/g9whPZY/LL0V8i870uEXGpjFtM8z2/osKK3VwQxRGgsZNPPtkKzc6onOrnsXMh3umug9BmhEwsUTEF3vNDScNzJcSaEFWMghuEDGdi4Vxw4WsRTzmXfNbT+XwhAOPFiccvxVvCHqL0z/nGczGqAAzvU+WVAin8S5T3MZHXYiZrz6atRLpsqOkaERABEYgfAYl08dszzVgEREAEREAEKp7A66+/HiRvv/LKK81hhx1m84+RvN4398Dse7whQFAh3Pe6wvvFCUOZwPOFKXLc+YUPMumnWG1Zp8vJhjCHqIWFCxEgjlG98sADD7RhfOkU1MDTyAlnTjjNZl1UkiWM1BkeegiyfpEDhEbmFTbfO5L3EBgJZWYtiYSXcB+EPrrCFInGyWZd6V5D+ClVT7FkuRKd5yjtwrwXL15ci0+mRVH88Gf6dyHi4TXAlqIVWDhk3D8P2QpX4bx68MArFj65hhlzzgilxWvQFX9hHeSUw+suleHpRy47wqnJx+jnxosK9U7VX67vS6TLlaCuFwEREIF4EJBIF4990ixFQAREQAREoKoIkOQd7yGMvFgkviffGmKAby5XF/ngbrzxRvsW1R4RbcLeY+QC8ytPhoHyUI/nEjmsXO49HubJfYdFJcYvxqYsXbrUegghYDRt2jThkF988UWQg45GfhELPIOOPvpoey0CHeGR4VxtrmPGwlOLirl+Di6/cqvvpZcNA7yuCBHGWBdjuVDaqIISbgz/Ojyt2JuoPGF4VbGXCD2ElPrmV24tRaVOcrfhzYclChMNV2YNh+WG38drzC/gkWpPPv/8c5trzRlCVqdOnWpdFvZ0C3uj+l52yXLrISjisUgeSX9MBuNzSlEJLJm3K+cRsYxqs34uPq5DMFu4cKEtCpHoTPsepuG5EiLLZ2WzzTarJR77MOgf4d8Z3niuEEsq1vl6n3yAeA/DqZi5QfM1f/UjAiIgAiKQHgGJdOlxUisREAEREAEREIEiEqDa6IUXXmhHJGcXQosfAuum4kQWP8G9C8VEpPHz6CFSITSFQ+cQdPCUwWOPapn+Qzzed4RnYn71ySKiCPLtEaoHF0StsFEggHBV5+1DW7yInIBFGJ+rjsu1UaIMnkMIm4icGAIlXkfOrrvuOjNq1Cj7I6HEYa/GTJj897//rSOeuevHjx9fqyCB3y+FLgh9xhAbWWO4WAH5DAl/JuQRo1gFAowzP3+hE3QzmXuubX2RLlGoadhrlEIP6667bjA0VUY33njj4OdMPbv++usvGxbMXLAo0fWZZ56pFSIe9jr0hXT64Ge/Ii2vuWqozhuP/fO9KPmsst9Yokq3FLWg6AmFQTjXiMiuCIVfAIMQaYSscOVV1ohHqauEGw7V9sPiH3jggVqfE+bF/YH8js6LNJXInev50PUiIAIiIALVTUAiXXXvf1mvHo8FvrkknKJRo0ZlPVdNTgREQAREIL8EfC8dJ7LwsNymTZtaA5HwnoTujz32mDnjjDPse4hxhKkiOhHO6Tx1eI+QPbzx8Kjj4R0PJK514Y+0QexyYpQv0pFAf9CgQfldaBq9+SGHNMebDK8evOrwnsNLCSHRiRC0oWKpHz7Ka8wdcQ5DTMHzEJ5U30TsgLkLlaUNOeJcRVh+9vOYIfA4D8M0lhDZxGfrGjCvJ598MmEOMs4A3liukivFABBQ/va3vxk8v6ZPn275+KGJvOYXWeCcsOdYKYTX+fPnB8UqCNd1BU+YD+ujeAEiozOKM7DGsPmholECWap9CYtscCHEls8T54E5uDMV5d3Ie4QkuzYIaAjriG2Ic4SKcsb89SGc+lWD+dwRfuyM6/n8klMQDzeEQb+iMGMg+DkhLlwtmOvJHYl98sknNv+cE9ndGFy/3nrrBWP6npXsB/y5P1CcAw87PD79/HbZhvam2g+9LwIiIAIiIAIQkEinc1CWBPywglKEFJQlFE1KBERABKqIwE033WQ92zC8pdZZZx37/37hADxaqJRJPjW/YqZfdICiBAh16Rrhh+Rvc+P5OekSiSXp9p1tO7+KZjp9IFKRyD9sH374YZ2cejD0xT13DaIMBTN435nvWZWsKmk6c6RNOGST19h3hKJk5lcmde0Qb6Iqe5KXEM8p3/wCFaUQXhGvEIb8ubvwRfbI3w/WRT61DTbYoA4SvwCGy8OYLnvaIc4iODmPw2TXJiqwgefZOeeck9aweDASlh428u09+OCDtV5OdC4RhhGInbHnhMD6luha2iC4ERbrW5RYnKgPzj2FavTlcVpbrkYiIAIiIAJZEJBIlwU0XVJ4Anzryh9zmES6wvPWCCIgAiJQbgSo0EioZbiiJA/pLum7/9BP+B6VPfF8obgAOaickYvupJNOCryvEq0VQWfAgAG1cntRbdR58pTSg4bQXdYVJai59eDBRDXXqHBY1waPoGOOOSZS0HJtKD6Bh5kLKXSv453GGFiyqqSZnCU/hBYPLvKOhcMVo/qbNGmSQWBLZuFwXdfWv/a0004zZ599diZTzrlt2HssUYd4dSGC+Z5nflvmzd9IWLa59fB448y4isDhubAn5AoM5/Vz7fjcEYJN1EMyg/PgwYMj9xbvQfaKarGJDNGMkPSwdyjtfQ/PRNezDs40An7YEIu517jQ30R94NFKHw0aNMj5DKgDERABERABEUhEQCKdzkZZEpBIV5bbokmJgAhUIYElS5bYL01atGhhq6sW0/A44uGa0DdfFPj0009trjW8j/yiAYQ7khCfEM5wtdLvvvvOhkLilUfRBAxvOTyUCB2luiheS2FDFEPUYZyePXuW1IOGuRDeh4D51Vdf2XA8wjhZL6JZOPF/or1ClMA776233jLvvfeeTbbfuHFjKwYhYtBXIsPLENGTMNN8JM7/+eefbWgxAuCxxx5bKzl/qrOG2EWVUrwl8cAn5JV/7du3tx6DnNko45zgsQdPxuSMFdN8sZNx8apjP2GBYMWeUiiFf2uttVbCqfE5oOIwa+7fv3/W4hFCG56o/O1FaDjiLGeKfHmEooZz/kVNCIELgZzPF96AfJaaNWtmttpqK1uplf9PZYShcj3nkiIu9MG5RCBkHsmKvlAxF09P+iAEnmtbtWpl//G5RVxOVsGYMzFlyhSb7478fuwRXrUUqUAYRKDzQ2RTrUXvi4AIiIAIiEC2BCTSZUtO1xWUgES6guJV5yIgAiKQNgH/fkyuMPJgyURABLInEC7igdgmEwEREAEREAEREAEISKTTOShLAhLpynJbNCkREIEqJKD7cRVuupZcUAJU4iXnnzOJdAXFrc5FQAREQAREIFYEJNLFaruqZ7J6KKyevdZKRUAEypuA7sflvT+aXfwIhIsdLFiwIGE12/itTjMuFIGxY8facFzy/7lCI4UaS/2KgAiIgAiUjoBEutKx18hJCOihUMdDBERABMqDgO7H5bEPmkXlEFi6dGmt4h4fffRRWsUyKoeAVpINAfLjYaWoSJzNfHWNCIiACIhAdgQk0mXHTVcVmIAeCgsMWN2LgAiIQJoEdD9OE5SaiUCaBFzBD9ecAikrr7xymlerWbUSkEhXrTuvdYuACFQbAYl01bbjMVkvVdqotofV1NTkpYJcTJauaYqACIhAWRGQSFdW26HJVAABqqlSSdeZq7BbAUvTEgpIQCJdAeGqaxEQAREoIwIS6cpoMzSV2gTGjBljEOuGDx9uGjVqJDwiIAIiIAIlICCRrgTQNWTFEzjuuOPMs88+a9Zff33z8ssvm/r161f8mrXA3AhIpMuNn64WAREQgbgQkEgXl53SPEVABERABESgBAQk0pUAuoaseAJLliwxs2bNMltttZVZe+21K369WmDuBCTS5c5QPYiACIhAHAhIpIvDLmmOIiACIiACIlAiAr5IN2PGDFUVLNE+aFgREIHqJiCRrrr3X6sXARGoHgIS6apnr7VSERABERABEciKwIgRI6w4169fv6yu10UiIAIiIAK5EZBIlxs/XS0CIiACcSEgkS4uO6V5ioAIiIAIiIAIiIAIiIAIVCUBiXRVue1atAiIQBUSkEhXhZuuJYuACIiACIiACIiACIiACMSHgBPphg0bJq/m+GybZioCIiACGROQSJcxMl0gAiIgAiIgAiIgAiIgAiIgAsUj8NBDDxlyhA4aNEi5QYuHXSOJgAiIQNEJSKQrOnINKAIiIAIiIAIiECcCCxcuNEuXLjVt27Y19erVi9PUNVcRqAgCy5YtM++9955p1aqVWXPNNStiTVqECIiACIiACEQRkEinc1G2BMaNG2d4MBo4cKBp1KhR2c5TExMBERABEahMApMmTTJXXnmlWbRokV3g+PHjTdeuXStzsVqVCJQxAbzHJk6caGe47bbbmksuucRsvvnmZTxjTU0EREAEREAEsiMgkS47brqqwAQQ57p06WJHqampMZ07dy7wiOpeBERABERABP6PwB9//GHOPvts8/DDD9dCMnr0aNOrVy9hEgERKDKBc88919x///36PBaZu4YTAREQAREoPgGJdMVnrhHTIEDOjT59+kikS4OVmoiACIiACOSXwBVXXGFuvvnmoNNjjjnG7LXXXmannXYyK664Yn4HU28iIAIpCfzwww/m2WefNZMnTzZPP/100H7ChAnBl7opO1EDERABERABEYgBAYl0MdikapyiRLpq3HWtWQREoBwJLFmyxAwdOtQmKqeqYKXbK6+8Yg477LBgmSRr33777St92VqfCMSGwHXXXWdGjRpl57v66qubV1991ayxxhqxmb8mKgIiIAIiIALJCEik0/koSwIS6cpyWzQpERCBKiTg349nzJhR0VUF//rrL3PAAQeY2bNn250+66yzzOmnn16Fu64li0D5EuBzetBBB5k333zTTpIvEc4444zynbBmJgIiIAIiIAIZEJBIlwEsNS0eAYl0xWOtkURABEQgGYFquh/Pnz/f7L333hYHHjqzZs2y/5WJgAiUF4GXXnrJHHnkkXZSa6+9tnnjjTfKa4KajQiIgAiIgAhkSUAiXZbgdFlhCVTTQ2FhSap3ERABEciNQDXdj++66y4zfPhwC+zggw82Y8aMyQ2erhYBESgIgd9//9106NDB/PTTT7Z/8tW1adOmIGOVS6eE3s+cOdMMHDiwoj2ay4W35iECIiACpSIgka5U5DVuUgLV9FCooyACIiAC5Uygmu7H/fr1C5LSk/eK0NdcjdC8evXq5dqNri8igTlz5phrr73WNGvWzJx//vlmpZVWKuLoGipdAohVkyZNss0vu+yywLMu3evj1m7LLbc05AglNyj3KpkIiIAIiEBlEpBIV5n7GvtVVdNDYew3SwsQARGoaALVdD/u3LmzWbRokd3Pp556ymy++eYZ7+3PP/9s7r33Xht+99Zbb9n+OnbsaI444gjTu3fvolWH/fPPP81rr71mPvroI/PJJ5+YxYsXmwYNGpi11lrL7LHHHqZTp04Zry0uF9x+++3m8ccft7ypzPvbb7+Zd99913ohIcC1bt3a7LbbbmarrbaKXNKBBx4Y5Dt75plnzPLly+21H3zwgVl55ZXNxhtvbPm1b98+8nq8u6hASrGVZJyXLVtm7r77brPeeuvZHGuyzAjcdttt5tJLL7UXIVpVemGbjTbayK4VcXLQoEGZwVJrERABERCB2BCQSBebraquiS5cuNB06dLFLrqmpsbw4CQTAREQAREoPoFqEel+/fVXs8kmmwSAyU+HqJWJvf766/YB+rPPPou8bIsttjD33HOPzaFVSGPPLr74YitMJbIJEyYEv2cLOZdi971gwQLTrVu3YFjEOqr1urBIfz433XST2XfffetMcZtttjHffPONfR2B1RUSCTccMGCAOfPMM+sIr4RJ44mHJRKPmE+vXr3MvHnzbLtsReFi8y2n8aZPn25OOOEEO6Xdd9/d3HnnneU0vbzPRSJd3pGqQxEQAREoSwIS6cpyWzQpCIwdO9Yg1vFtYaNGjQRFBERABESgBASqRaRDWNtll10Cwp9++mlGtN955x3Ts2fP4BqEOL5s+vjjj2uJZQiBTz75ZMFCKG+++WZzxRVXpJw7Ih5eZpVm/nlNtTaKgiCshsVYJ4akup73R44cafr27Vur6T//+U8zevTo4LWzzz7bnHbaacHPeDn279/fTJ06NXiNIiXrrrtuOkOqzf8jQHVXvB4xvCOfe+65imYjka6it1eLEwEREIGAgEQ6HQYREAEREAEREIGEBKpFpCMMskePHpbDhhtuaF588cW0T8Uff/xhwxWdxxXeWVdffXVQGXbixIm1wtMKJZARXuvn0SNcd8iQITbBfv369W3o66mnnmq9xHgP761KM8JMo/J1UbWXMF8M0czZ9ddfb/bff/9aGMIiHeItobN41X3//ffmrLPOsqGvGGIsobB+3jr4cgZc6DTtCMHt3r27vebGG280V111VTAmZ+XQQw+ttK0o+HoI4951113tOAiuc+fOLfiYpRxAIl0p6WtsERABESgeAYl0xWOtkURABERABEQgdgR8kW7GjBkVW1UQTyaEGAxvN8SedO1f//qXDXt0og0CH6KBM3KaISY40ebYY481I0aMSLf7tNpR7ZI8ay7UFq8+PLpWXHHFWtcjHhEGu/766xv2ttKMQgKEHPvmC2S8TgVfKvli7BtCpm++SEcBEUQ8v/jHhx9+GAh+XHfLLbeYffbZp1YfhN1SIdiFzfIm4ZlLly61rzurhlxqhTpjX375pdlxxx2D7jP1fi3UvArVr0S6QpFVvyIgAiJQXgQk0pXXfmg2IiACIiACIlB2BEg/QNqBQw45pOzmlq8JvfDCC+boo4+23ZE77oknnki7ayqAUiwC873kKCJBaCv5yfw8dRQLcB5AaQ+SoiGeXXvuuadthXcX61ljjTXqXPX3v//d5kGjDcUtKs3I+XfhhRcGy4rKO/fII4+YwYMH2zZ4HiLE+eaLdHhr4YUYNj4Lr776qn35lFNOMeeee26dNnAm75zLh4cwSu5DJ9zttNNOZvz48UUrJlJpe/3111+b7bffPlgWoeUrrLBCpS0zWI9EuordWi1MBERABGoRkEinAyECIiACIiACIlD1BF555RVbYADL1JMOIYZKqhgC3C+//GI98R588ME6XMlN5odb5gv8Y489Zs444wzbHWLjJZdcEtk1Qh6CXqWKdIhyV155pV07a0VgDpsvyCLyPPTQQ7Wa+CIdIcJhb0QaIwQiCGKEseKtF2WJcuQh2E2ZMsU0btw4X0eg6vqRJ13VbbkWLAIiIAJVQUAiXVVssxYpAiIgAiIgAiKQjICfhD4TAYsiAK1atUoJF++8YcOGmR122CFl22waUCyCohFYVJ411ychsXgcZbLGbOZTqmuuueYau35s6NChgXDpz4dwX1fVNSr/oC/Svffee2bVVVets5zbbrvNXHrppfb1KKHPv+DWW281l112Wa0+VM019xOCpyKeoVg15KTjHkK4NPeRqLyLuRNVDyIgAiIgAuVAQCJdOeyC5iACIiACIiACIlBSAmGvHEJBEbJS2bJly0zbtm0TNqNgwXHHHWc6d+5cK69Zqn4zff+kk04KqoVOmDDBVpaNMoogEHpbqaIG1Vad99x5551nTj755DoYwntN/jg/55wv0lGMwM8v6DpjDMbCkhXhWLJkiQ2pRRj1raamxp4JWfYEHn30UTNgwADbQaber9mPWror8fjEM3PQoEEVmxu0dHQ1sgiIgAiUDwGJdOWzF5qJCIiACIiACIhAiQj89ddfpn379kH+sAceeKBWUvpk02rXrl1wHe3weOnTp4+tFtukSZOirIgQWoQfDC8vxMGwUYV2yy23tHOtVJHuggsusHnesHPOOcdWsw0buQIR1py9/fbbZs011wx+9kW68Huuke+5SG65+++/v844CLgUCYkq0AF/Co4gLsmyI+DvATkC8aKUiYAIiIAIiEDcCUiki/sOVvD8x40bZxYuXGirtJGwXCYCIiACIiAChSRwzDHHmH//+992CMSeE088Ma3hqP45e/Zs25bKoccff3zkdd9//7157rnnzDbbbGN8ISjRIOSOW2mllUzLli1TzmPMmDG2QAUWVbGU1yl04Ip/pCvSZTKHRJMkXx4hpgcddFAtcSzlorJocNFFF5k777zTXpmooAPv+fzDoaf+e4k8Kl0BDvqKqtBKXkK8G59//vlgFVTbxfvOFY4gLx1C3XrrrZfFSrO7JNf9RHgkT1+LFi1qCZuZzCbXObixEMKdAArXvn37ZjINtRUBERABERCBsiQgka4st0WTQpxzoToKCdF5EAEREAERKAaBivxK4wAAIABJREFUq6++2txwww12qGQhjOG5+N5bhJO6Sq9+O4SNI4880ixatMiG0c6cOdMKcIlsyJAh5uGHH7Zv4231+OOPmwYNGiRsj+cfnmOuPVVl/f7xniPsEoEESycnXaZziJqcH1qKKBXlVZbPvR09erRBDMOOOOIIc/nll0d278J+eTPseeiLdAibYRHNz1/I9XfccYfZa6+9gnF+//13KxBOmzYteA2vr8MPP9zMmTPHelg645xRYKQYX0bmup9vvfWWZeqq1V511VXWYzQTy3UObqxwyDKhoH6l10zmpLYiIAIiIAIiUE4EJNKV025oLgEBvxqaRDodDBEQAREQgWIQwOvJ98aZPHmyDQ9NZeQboyCDMyp/UmF1lVVWsV5TiG1+4QAEMsSfqKqh9PHSSy9ZQc83vOTwREtkixcvNtttt13wNoIQHnUIe3iD4WFGLjpnqQSzbOYQNTfEEwo4YFFFGlKxzfT9u+66y3ozYoT8IsBF2VFHHWVefPFF+1bYC8sPX6bq7wYbbBB08c4771gPS8RWDAEVMa5+/fpBm4svvtgKd87CHn0IqP379w/eJzcdlWI5L4WyfOynX8WYeXKG4OPn80s2/3zMwfWPmI6o7ixR7sBC8VS/IiACIiACIlAoAhLpCkVW/eZEQCJdTvh0sQiIgAjkjQCJ7xExmjdvbtMPVLJRqXWPPfYIkvzjeXbdddelteSzzjrLekT5Rkip8zryX7/lllvMPvvsk7Bf/3ega5SsYqtrc9pppxmExXSsdevWNvQ2kWU7h3B/FM149tln7csIl5dcckk608u6zRNPPBHkodt2223NI488EtmXv1+DBw8OChDQ2Bfp2EOq966wwgoGIdSJc67Tu+++2+y6667BGGEPL6rIsndc7xvXUaXTGcIe4daFsnzspx9eyjwRXV944YW0Rbp8zIFxf/zxR9O1a9cgbJjiIBQJkYmACIiACIhAJRCQSFcJu1iBa5BIV4GbqiWJgAjEkoB/P54xY0bFVxX0Pb/YsJtuuskgtKQyQhwJrfQ9qMLXIPjcd999Zuutt07aHWIhIZHz5s2z7RDU8L5addVVk16H1x550F577bXIdj179gxEvGQCFhdnOwd/YHLwdezYMXjp9ttvN927d0+FMqf3fa/GRAUdGGDKlCk2JBW78sorzWGHHRaMS85Alzcu2WTCAh1t2TPy1WEUEMGLMlGY8qhRowIRGIEOoa5Qlo/9JHefXy2XQg0ux2E6887HHBgHz0w+p87C3o7pzEVtREAEREAERKBcCUikK9edqfJ5SaSr8gOg5YuACJQNgWq7H5Pwv1u3boHHFMIa4au9e/dOmkPObRhhrIhk5O/64YcfbO63xo0bG0QxQmL9KqLJNhnRjyIWVGTFU2vllVdO60wsX77cevRRyIJ/TZs2tWLRVlttZcNhEaCw3XffPSiwkKjjbOfg+qPi6bnnnht0X6yQxAkTJphPP/3U7lmi6qmsDZFt6dKlttCHnxPOF+nIGQd72nHNuuuua/bcc08rxOFhF2UTJ060uecIN06133y+2GfCrNmrQlqu+8ncyBnMGUd8bdOmTcbTzWUO//vf/8zNN99cSwjHu4/ceDIREAEREAERqBQCEukqZScrbB3V9lBYYdun5YiACFQQgWq8H+ONhcDje1Mh1lGldOONN47t7vqhoFEVSfO9MDwQqeqKIWyNHTs230MUpD9yxLmw1nTzEhZkIuo0IBAOD+YNin/gnZmsoEolIZw6dar11AyLypW0Rq1FBERABETAGIl0OgVlSaAaHwrLciM0KREQgaonUK33Y6qxEsrnC3Ukqj/00ENjeybw1qI4BhYVqpnPheFJSE4/ZyT632+//fI5RMH6wuMRoRZ79NFHU4YnF2wi6jggEM63WG0CHSAoYkOOUHIZIrLLREAEREAEKpOARLrK3NfYr6paHwpjv3FagAiIQMURqOb7MaF5hK4ibBFGSoEBPywyTpsdroY5f/78gnogISI8/fTTASI8gFZbbbVYIMPr74MPPrBzJXS1U6dOsZh3JU+S80O+x7Zt29pw9E033bSSlxu5to022si+TgGfQYMGVd36tWAREAERqBYCEumqZadjtk5ynnTp0sXOuqamxhB6IhMBERABESg+gWoW6YpPO/sRyaX30ksvmQ4dOph11lkn6AhPQCrU3nXXXcFrVFy96KKLsh8sxZXhCqd4QZ199tkFGy/fHfthuuT322GHHfI9hPoTgYwJSKTLGJkuEAEREIFYEpBIF8ttq45JjxkzxiYoHj58eGw9F6pjp7RKERCBSiYgkS4eu3vLLbfY6rIYnmDkziNkk4q8P/30U7AIClg88MADaRXByHbljEeoK95oBx98sLnkkksMOf3iYr169Qoq5MJqxx13jMvUNc8KJiCRroI3V0sTAREQAY+ARDodBxEQAREQAREQgYQEJNLF43DgLTdq1Kikk91pp53M9ddfb5o0aVLwRREq/Ouvv8YmxNUHcswxx9iKqxiVYp1nf8GhaQARSEJAIp2OhwiIgAhUBwGJdNWxz1qlCIiACIiACGRFwBfp8Mpq3rx5Vv3oosISQBC7//77zfjx44N8am7E7bff3hByuuuuuxZ2EhXSOxVD8f7DEOtatmxZISvTMgpB4J133jE9e/a0YeYUm+Ff69at8z6URLq8I1WHIiACIlCWBCTSleW2aFIiIAIiIAIiUB4EqCZI+gHEOVUULI89STULwk1JF0GRi6ZNm5p69eqlukTvewTwApw5c6Zl16ZNG7ERgaQE+CJjyJAh9jPnbJtttrFi3f7772/WWGONvBCUSJcXjOpEBERABMqegES6st8iTVAEREAEREAEREAEREAERKBcCXz33Xdm2rRpZvr06fafb+Rn7N27t+natWtO05dIlxM+XSwCIiACsSEgkS42W6WJioAIiIAIiIAIiIAIiIAIlDOBDz/80Ap1iHZvvPFGMFU8MxHrqB7crl27jJfgRLphw4bJqzljerpABERABOJDQCJdfPZKMxUBERABERABERABERABEYgJgVmzZpmpU6da0W7BggXBrLfbbjtbAbl79+5mvfXWS2s1Y8eONYTWDh8+XLlB0yKmRiIgAiIQTwIS6eK5b5q1CIiACIiACIiACIiACIhATAjgWffUU09ZD7ulS5cGsz744IOtWMe/FVZYISar0TRFQAREQAQKRUAiXaHIqt+cCVx77bU2CS9u/SS/lomACIiACIiACIiACIhAnAlQifnRRx81TzzxhHn++eeDpWywwQa2SixiHZ52MhEQAREQgeokIJGuOve97FeNONelSxc7z5qaGtO5c+eyn7MmKAIiIAIiIAIiIAIiIALpEvj666+tYDd58mTz9ttvB5dtu+22gXddq1at0u1O7URABERABCqAgES6CtjESlwCOTf69Okjka4SN1drEgERiC0B7s2vvPJKbOeviYuACIhAuRL45ptvzLx588z7779vlixZEkyzdevWBqHu+uuvN6uvvnq5Tl/zEgEREAERyBMBiXR5Aqlu8ktAIl1+eao3ERABEciWAA+LQ4cOtYnKGzZsaEhFIBMBERABESgugb59+5qRI0cWd1CNJgIiIAIiUHQCEumKjlwDpkNAIl06lNRGBERABApPwL8f33DDDeajjz4q/KAaQQREQASqkAAVYOfPn2+96f744w9LYLXVVjNNmjSxRSfkSVeFh0JLFgERqDoCEumqbsvjsWCJdPHYJ81SBESg8gnoflz5e6wVioAIlI7A7NmzbV66KVOmmK+++spOZNVVVzX77LOP2Wuvvcyee+5pVlllldJNUCOLgAiIgAgUlYBEuqLi1mDpEtBDYbqk1E4EREAECktA9+PC8lXvIiAC1Ufgs88+M5MmTbLecXPnzg0A7LHHHoEwt84669QC89BDD5mZM2eagQMH2vQDMhEQAREQgcokIJGuMvc19qvSQ2Hst1ALEAERqBACuh9XyEZqGSIgAiUlQH5PPOamTZtmXnzxxWAuHTt2NPvuu6/1mGvTpk3COW600Ub2vWHDhpl+/fqVdC0aXAREQAREoHAEJNIVjq16zoGAHgpzgKdLRUAERCCPBHQ/ziNMdSUCIlB1BCZPnmyFuenTp5uff/7Zrn/99dc3Bx98sPWa23rrrdNi4kQ6POkGDRqU1jVqJAIiIAIiED8CEunit2dVMWNc/8nFgdXU1JjOnTtXxbq1SBEQAREoNwIS6cptRzQfERCBcifw8ssvW1EOcW7hwoV2uiuuuKIV5nr27Gm6deuW8RIk0mWMTBeIgAiIQCwJSKSL5bZVx6SHDBliCA0YNWqUadSoUXUsWqsUAREQgTIjIJGuzDZE0xEBEShLAu+9917gMUcxCGe77rqrFee6d+9uGjRokPXcJdJljU4XioAIiECsCEiki9V2abIiIAIiIAIiUFwCEumKy1ujiYAIxIvAp59+ai677DJbBMJZu3btTK9evcx+++1n1ltvvbwsSCJdXjCqExEQAREoewIS6cp+izRBERABERABESgdAV+kmzFjhqoKlm4rNLIIiEAZEnD3SKqx4jHHv7Zt2+Z9phLp8o5UHYqACIhAWRKQSFeW26JJiYAIiIAIiEB5ECDtwIgRI6w4p2Tl5bEnmoUIiED1EZBIV317rhWLgAhUJwGJdNW571q1CIiACIiACIiACIiACIhATAhIpIvJRmmaIiACIpAjAYl0OQLU5SIgAiIgAiIgAiIgAiIgAiJQSAIS6QpJV32LgAiIQPkQkEhXPnuhmYiACIiACIiACIiACIiACIhAHQJjxowx5L8bNWqUcoPqfIiACIhABROQSFfBm6uliYAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIxIOARLp47FNVzvLaa681CxcuNMOGDTONGjWqSgZatAiIgAiIgAiIgAiIgAiIgAiIgAiIQHUQkEhXHfscu1UiznXp0sXOu6amxnTu3Dl2a9CERUAEREAEREAEREAEREAEREAEREAERCBdAhLp0iWldkUlQM6NPn36SKQrKnUNJgIiIAIiIAIiIAIiIAIiIAIiIAIiUCoCEulKRV7jJiUgkU4HRAREQATKg8CSJUvM0KFDbaJy0g/IREAEREAEREAEREAEREAECkNAIl1huKrXHAlIpMsRoC4XAREQgTwR8O/HM2bMUFXBPHFVNyIgAiIgAiIgAiIgAiIQJiCRTmeiLAlIpCvLbdGkREAEqpCA7sdVuOlasgiIgAiIgAiIgAiIQEkISKQrCXYNmoqAHgpTEdL7IiACIlAcArofF4ezRhEBERCBZATGjh1r5s2bZwYOHCiPZh0VERABEahgAhLpKnhz47w0PRTGefc0dxEQgUoioPtxJe2m1iICIhBXAhtttJGdOrlB+/XrF9dlaN4iIAIiIAIpCEik0xEpSwJ6KCzLbdGkREAEqpCA7sdVuOlasgiIQNkRcCIdnnSDBg0qu/lpQiIgAiIgAvkhIJEuPxzVS54JLFy40HTp0sX2WlNTYzp37pznEdSdCIiACIhAOgQk0qVDSW1EQAREoLAEJNIVlq96FwEREIFyISCRrlx2QvOoQ2DMmDEGsW748OGmUaNGIiQCIiACIlACAhLpSgBdQ4qACIhAiIBEOh0JERABEagOAhLpqmOftUoREAEREAERyIqARLqssOkiERABEcgrAYl0ecWpzkRABESgbAlIpCvbrdHEREAEREAERKD0BHyRbsaMGaoqWPotqdoZfPTRR2by5MlmwYIF5rPPPjM//PCDOeqoo8yxxx5btUzisPDXXnvNPPnkk+aXX34xv/76q1m+fLlZtmyZqVevnjnuuOPMjjvuGIdllHyOEulKvgWagAiIgAgUhYBEuqJg1iAiIAIiIAIiEE8CS5YsMaQfaN68edVUFPzxxx8NwsKnn35qhaCNN97YdOjQQQJliY7wBx98YK644grz9NNP15nB2muvbd54440SzUzDpkNgl112saJqlJFzmNzDstQEJNKlZqQWIiACIlAJBCTSVcIuag0iIAIiIAIiIAI5E/j999/NbbfdZm644Qbz008/1emvf//+5swzzzSrr756zmOpg/QILFq0yOy7777mm2++ibzgvPPOMyeffHJ6ncW01cSJEw1ehL169TKtW7eO3SpOO+006wEZZeztTTfdFLs1lWLCEulKQV1jioAIiEDxCUikKz5zjSgCIiACIiACIlBmBAi/O/300yO9tfypduvWzdx99902VE9WWAKIpj179jTz5s0LBsLz6owzzjDt2rUzjRs3LuwEyqB3zmXbtm3tTBCH58yZE8uzR4jyn3/+aef+2GOPmdGjR9s19enTx1x11VVlQLr8pyCRrvz3SDMUAREQgXwQkEiXD4rqQwREQAREQAREINYEzj777Fphd4MHDzZ77rmnzaE1YcIE8+CDDwbru/TSS20uNFlhCbz33nume/fuwSDsyYABAwo7aJn1jkcngqSz+fPnmwYNGpTZLDObDuGtfN6wvn37mpEjR2bWQZW2Hjt2rCFH6PDhwxV6X6VnQMsWARGoDgIS6apjn7VKERABERABERCBBATwTurRo0fw7tVXX20OPfTQWq0vvvhic8cdd9jXlAetOEfpoYceMkOHDrWDbb/99lZErV+/fnEGL5NR8D5r1apVRYl09957rzn//PPtmghVJmRZJgIiIAIiIAIi8H8EJNLpJJQtgXHjxpmFCxeagQMHmkaNGpXtPDUxERABERCBeBO47rrrzKhRo+wi1l9/ffP/sXceUFIVW9suFBGRIAqmDxUUBFEUwQAORhQxA8rFnDBHUMyKYsKEGYwYMSAgKgoCBhTBi2JAxYCCIpgVRMyI/Oup76vz15w53X16pnvmdPe712J5p7uqzq6navrSLzu89tprpnbt2uU2RTMJhCJXq27q1Klmww03rJaNr1ixoiBTHKsKZ+DAgTa1GDv//PPNySefXKUl6Spap06dghP6XJojm6c2XfhuZguFNGLu1CqrrJLt1GD877//burVq1ep+ZwpZ4sRGUmEpEwEREAEREAEROB/CUik001IJAHEubKyMusb/3JODRqZCIiACIiACOSDACl3U6ZMsUtTH4s6WVF2yimnmOeee86+hbB3wAEHBMNIQ3v//ffNnnvumVK8o/nB6NGjzWabbWZ22mmnlFtBQHn66aetWPjuu+8aupvSMIAi+8cdd5xZY401Us5FAKHmV48ePcwRRxwRjOPZdKz97rvv7J911lnHHHnkkeXWmThxon0eUYR+9FbUw0i7hMHmm29uaAyQS0NEwkfSih3viy++2DIjssz9Qaxq3bp1WtENhhMmTDAzZsywHDHE1u7du5ujjz7arLzyypGuk+Z85ZVX2np4RPNtv/32wbjPP//cvPfee+b777+3DS34O8ouu+ySSwR2LdZHFPbX5rkIjQhs2Yh18+bNM48//rh566237D3AtthiC+s7QlmmfwyFOSnf06ZNM2+++aahoQcRpVtttZW9Z7vttlvs/d9zzz2WLQZbagxmY4sWLbK/r/zOLV682PCzOwvuJGnqMhEQAREQAREoVAIS6Qr15Ircb/7i5b4kSaQr8sPW9kRABESgBgkgPiBWuAg56qDVrVs30qM77rjDXHPNNfY9vz4aQk2HDh3s61tvvbV56qmnIuf7kWEIYq4hgD/466+/tlFjr7zySuQaNA947LHHrDgSNuZ27tzZvuyaDCC6ITxOnz69wvjnn3/eCoYYAiNNGjBeQ9hK1RwDEXGvvfYKGjogPG677bY5OUXEMYSjVN1cww8hbfKEE06o8Ozly5dbEfHmm29O6RfPYQyCZdgQSenkiyGODh061Aqnt9xyi0Hw8g3W8Esl+FUGzEMPPWQuueSSjFN5Nvd10KBBZr/99oscz12LYuQGEz3K3ebuRtmSJUvsfX/hhRdS+oPgyVkgIGYy//fovPPOM4jfceyzzz4zl112mSGKNZUhaLroyzhraowIiIAIiIAIJI2ARLqknYj8sQQk0ukiiIAIiEAyCPzyyy+2sHuzZs1s+YFiMwSXXXfd1W6L9NV0AgDiGAIadvzxxxuiuzB/DUSTDz/8MBKTH4mHeNSzZ89y4xAKd9xxx3ICFWIYIklYZEPEa968ebn577zzjo2gc0aEG+JSKvNr7xFh1atXr2AoQmMq0QZfDjnkkFhjs70vP/74o+nYsWPsaWeffXYgpvmT/BqCvA5XRFHqD/osaUxBZFfY7r77bhvJhxF5R7OGVMIpY4jsyhR9GHtTxlgx6v777489hahOBMewhQW6Vq1aGToUEwnnohSZQ1QcUXLhphSInYiUfoddxNymTZvaSE8XncgaCIWIdZnstttuMzfccIMdxu8Qv0uZjL8XHnvssYGY7o/nd86J7O73MZeCaSbf9L4IiIAIiIAI5JKARLpc0tRaOSMgkS5nKLWQCIiACFSJgP95zJd4xLpiMoQKF8mTSrBx+yWN1KXmHXrooWbw4MH2rTlz5pg99tjD/m+ikmAWZaT20QwBQ0QKp5sSpUeUEYaYQqMKJ8Qhkhx44IGBGIFwMmzYsHKPefXVV8uluPpvIqoROUbtvS+//NK+dcEFF5iTTjrJ/m/qtREN6MQOutc6kSq8F6KyEH/cfqNq+FXljiCaIf68/fbb5VJUu3TpYlZddVUbOUbEVpMmTazgxGu++SUzwvvkZ78hBT8TIde+fftyayBg3n777RW2gZhFOjBptr5onU7UrAwLhF8aLJDKOXbs2GCJgw46yCCcuT9EgiKskbId3gNpw9xLF/lHGuhdd90VpMnOmjXLiq3uzKMEM//O4wQpry71l/XpNIqfGGIZqbD8N50hUN900012CPMR39LZsmXLTMuWLYMhrI8ATYotvydLly4tt3cEZ+6GTAREQAREQAQKkYBEukI8tRLwWSJdCRyytigCIlAQBIr985g6XaTcYX50XNThvPjii4Gg0Lt37yAayO8OS+24l19+OfJsSV8kjRHjf1NfzhnCGdFezsaPH2/rvTkjxbR///6BYBP1nHHjxpnTTjut3LMRMYhccmmtfoQZXTXpruksLEwhDIabAyxYsMAgljkjyhKBKB9GFCCpupifXpzpWaRdOuGIfZPWGzbOetKkSfZlIsPCEYcIVg8//HC5aUQ1Xn311WbNNde0ryN6uUiyXIt07sGkeHbt2tX+mCnSM7zHsMAWJV498MADVijDEL8++OCDoMYfAiAiqBN1ua/hFNywuIuwi8Cbzm688UabNozFuT9vvPGG4ffNWVTTFsRmUrQx9tCgQYNM10Tvi4AIiIAIiEAiCUikS+SxyKli/1KoExYBERCBQiFQ7J/HvkhBdM65556b8mgmT54cCGtENLmOsH6qKKJYqtpdiCE8Dwt3K/UFFZpPkG6JETFFBCMRdn6aZpSvjzzyiEF4c4YvRGH5goX/HKIIqcfn7KuvvjI77LBD8HNUSq4f7Yeog4BSv379vFxnvy4bnV1dqnGmhyF2OmGJOoB9+/atMMVPA40SPOH77LPPBvMQiRAx/Tp9Tgwkuo5owsp2O023H/9upRIcU833hUYExeHDh1cY6tdT5E1fyPv222/LNcyAR7t27SqsgdDm1j7mmGNsqm46I9UV4RiLiigNz/U/g3iPaFaE1U033TQQFH/++WfbGGPLLbcsd4cz3ZVCep8IUBqgEMFZbBHNhXQO8lUEREAE8k1AIl2+CWv9ShEo9i+FlYKiSSIgAiJQAwSK/fPYL2KfKZLOj1SjuZGL8nr99dfNwQcfbE8nnZDiR7GFu1r60UW8RyMGIvJIxaR+mG8IadQrCze4IJWRSC9n+LX++uuXm0t0FF/0EZYQOcLmRySRHkvzJmekReKXS49ELMHXfBkCo0spJVoPMSiTkYK5ySabBMOefPLJyBp3pHruv//+wbgvvviinADnd/xFyCRSjo6qvv3+++82tRlhKF/plS+99JJB+MK22WYbM2bMmEwIgvdJZXXCblgUdoOI0PRrG/pCHKmriNHO5s6dG9lR1u/WmkoM9J3m98ZFLsYR6ThTGPt151gPkbisrMymcdP5F1G6mA2BlBqhqYTnYt679iYCIiACpURAIl0pnXYB7bXYvxQW0FHIVREQgRInUOyfx76w5aewRh27nxrrp/75jNJF0iGg8TwM8Yn0VWd++mWqK4ewRh05GjxEFcb3a31FpSbGucrhqCU/7dYXY1iLmnH4lC/zIxcznY3zIZw2jCC57rrrVnAxXLfuvffeM40aNQrGUf9v5syZ9meiGolurAkjVdelJGfbuZQag65LLvX1UnV/ReRyQjDiL7XeMAROd0fTpdr6YiqCpt+QIoqZH40Zt9kETVG4+34Di/DaNPigkQj7KUbbaKONIj87inGv2pMIiIAIlDIBiXSlfPoJ3rv/l2f+Fb9Y/8KV4COQayIgAiJgCRS7SEdkEvXOMD8K7uuvv7b142ju4KLR/I6ffo00P+IonZjhixPhdFVfFApfva222srWwqMmWrhJgj/2yiuvDDqVxu2aGX4WkVU8x4khrmsotceI4HOiT6aow1z8+vgRilF146KeQY04ormcpWoiEBYj6cjrNzzo3r17wCCqsUQu9hdnDT89OapZSLo12rZtG0SfIQ6zp7D98ccftuutM+rwEZWGPfroo1YYw9LVWqS+HJGgGHcVn9PZtddeGzQ9CddmzMSE+o+kFlOXLlUnZhqqwKrYTCJdsZ2o9iMCIiAC0QQk0ulmJJYAnb8Q66jh07Bhw8T6KcdEQAREoJgJFLtIRwSVH2HkxBrXidVPMSTN7MEHH7THTX0yunxi7777rkHMwhB6WCPK6AZ755132rfCItcZZ5xhU1ud0SWW6DFSMuOm8fn+nXPOORWaSMS9p370FnPoGosw4te7oxbdOuusE3fJSo3zU1KJ7iLKK5ORguqaZDCV+Pk+AAAgAElEQVSWOn1+ows33xeWiAYkKtC3XXfdNeiKOnr0aJvmWxPGneBuYE4wjetHjx49DBFoGGsQZRa2sFj5yiuvBOmvnPlhhx0WTAkLme4N7in3AYsT8ejXpKOuH92CK2N//fWXbRJBtOdjjz0WCJLZNtiozLNrYo5EupqgrmeKgAiIQPUTkEhX/cz1RBEQAREQAREoGALFLtJR54qII2cu/c6JdLxOnS6EH9LpXCSZ383T78DJ+KjaXdTVOuWUUwwNC7CwSOd3ViW1EjFvpZVWqnBPWIfGFNRAQ0D0za95l02jhfBDaFaBD65zKbXNpkyZEqREHn300QZO+Tai+Vz0V7g+Xrpn++mbqWqx+cJSt27dgghEt67fuRVhllTTmjA6llInEMu2cQRNUFxNQbq0us7C/j58sZLXP//88+DehTv5RtX3C0fi8Q+rRH2mM/4RltRsLNX5+PP5/SIikoYg4RqLbhxNFfz6iNzdOnXq1MSR5e2ZEunyhlYLi4AIiECiCEikS9RxyBkREAEREAERSBYBX6Sjy2gxdhX0O3kSVYUo57oochoINAh0rlEEkTpEl7lOn+EOmb6AR6MG0jYRL5zoxZphkc5vSkE0HvXQwt1Cf/31Vyv0Ee2ETZo0ybRu3Tq4MLfeemvQcfbwww83V111VaUvE3XFeFaURTWkqPSD0kykmQPiEhYnjdIt5af9ImQiVNWuXTt4Uvi8oqIOaQzC3cfoROo3mcjHXlOt6QuVjMkm9dav6cedohGJH/2I4Et9QyIWMdKZiUhzFk59jhJ+X3zxxXKiXJyoQ3gSTYeFG6iEOfiRkUSXsv9wBOeiRYvs75OrIRg36rI6zzEXz5JIlwuKWkMEREAEkk9AIl3yz0geioAIiIAIiECNEaCbIJEviHN9+/atMT/y+WAi31yxfJ6DCEcU0mmnnRb52Kg6Wn56JEIfNdS+//57K+aFu1KyaFikQzAhLdMV8Ce1kW6ma6yxhiFaCcGFaDsaIzjjNb9Dq19DjLpyLrW2MuyIpiOabN68eeWmx+2yWplnMgdREzGJ5+IDKcIYTPnfdFglQoo/dPwMd7hl7Lfffmu23377wAWiAkmpJBIN4Y+zJU0SQ7xCfG7cuHE5l+lc62qrxelAWtn9Zpq3bNky07Jly2AYteGIrHM1195//30r2tJIBLHRN1gSJejEYeYiFiN48ntNM4knnngimIJAh1DnWzj1GS48m98RajEi5Lr7jZBNRJtvrI9/1DTEOD9SY11EKr4QIcd5IqTyXyIh6WSKIcBtvfXWwZLca/xm7OLFiw3iNlF5bj0Gpqq/l4l10t+XSJf0E5J/IiACIpAbAhLpcsNRq4iACIiACIiACBQwAT8KLd02ECIeeOCBck0GGE8aa6baWghCTtCIarzgd9N0PiBO+QKEez1qvh/V5NfSq+yx+NF9bo18R9EhOiFwxrFUKZzMHTp0aBD5mG6tVI0L0nXijeNbLsdw3xDXMlk4spLx06dPN6QrZzIE2eHDh1cYhlB6zDHHBNGb6dYJR/mFU2Ez+eDeJ2LORTHyGlGMLtqPn/3fo/Ca/EMCTVOiUsXjPj+p4yTSJfVk5JcIiIAI5JaARLrc8tRqIiACIiACIiACBUrA76QZtQUEM6KuVltttcgdUvML0SdsiE4IBwh5Tmyha6arNeaPHzt2rOnXr19agkSUHXrooRXGEGVHVBKWTXpoqoeFRZbqqEUXTu9MB4K9jhgxIuUQOpXCPZWRvkzzD5e2nOocwp14q/t6k3ZKZ+B0kZFbbLGFTQX103qdn9RzO+KIIyIjOhlz3HHH2bTTVPeaaD5qx5HKGmVE1RFtG66RyFi/S25cbmGBmeYXNLCIikh1ayLcnXnmmebEE0+M+5iCGyeRruCOTA6LgAiIQKUISKSrFDZNEgEREAEREAERKEYCRK0RtUPH1q+//tqmXBLh5oxoI6KOUtl3331nU1wRuDbffHPblMKJH0uWLLENCniPtEFSWaOMVE86ayJO0OWccfxhva5du5oNNtgg5fNJWaRjLemypA1Wxfz0WdYhuokop3zb7NmzbYdcuneSBswZkLqJmEaEFKmddH0nxTgVQ+fj/Pnzrd+kZlLfrEWLFoa0z86dO6dsQsBczmjYsGFWGEKcRIiqaZszZ46hkQSpuqSr1q9f3yDctG/f3oph6RolkBoKByLruOOcIyxIJeVeZTKEQqIcWYPfD9JWN9lkE8uScwjXT3TrcX78HnF+rMEf/rf74352Z0z6MnUWw8IpKcyk3pIqSxMTDP+bN29u6xYihKfyIdPeCuV9Pnvgj9BfjLVBC+Uc5KcIiIAI5JuARLp8E9b6IiACIiACIiACBU3A75pKxA7dVVN1mSzojXrOU0OM+mQu1bY6ouiKhZ32IQIiIAIiIAIiIAKVJSCRrrLkNC/vBO677z4bQUDaD/9iLhMBERABERCBmiBANBURbK6pA9FHFMRPF7lUE37m8pkPPvigGThwYLAk3W7XXXfdXD5Ca4mACIiACIiACIiACIQISKTTlUgkAcS5srIy69vIkSOrnLKTyE3KKREQAREQgYIhQMOEgw8+OPA3qnFDwWwmg6Okenbs2DGoAUbNsqhae8WyX+1DBERABERABERABJJCQCJdUk5CfpQjQM2NPn36SKTTvRABERABEUgMAT/ttVWrVjbttRjt3nvvNezVGXXA1llnnWLcqvYkAiIgAiIgAiIgAokiIJEuUcchZxwBiXS6CyIgAiKQDAIUqL/88stt2QE//TEZ3lWvFzQyIKKMCO9bb73VNmcoNiO1d9tttw2i6Io5YrDYzk77EQEREAEREAERKHwCEukK/wyLcgcS6YryWLUpERCBAiTgfx5PmzZNXQUL8Ayzcfmhhx4ql9pKV9S11147myU0VgREQAREQAREQAREoJIEJNJVEpym5ZeARLr88tXqIiACIhCXgD6P45IqjnHnn3++eeyxx+xmTjrpJHPBBRcUx8a0CxEQAREQAREQAREoAAIS6QrgkErRRX0pLMVT155FQASSSECfx0k8lfz59Omnn5oTTjjBNGnSxNx9992mcePG+XuYVhYBEYhNYNSoUYYuy/369VNEc2xqGigCIiAChUdAIl3hnVlJeKwvhSVxzNqkCIhAARDQ53EBHJJcFAERKHoC7dq1M9QIpTZo3759i36/2qAIiIAIlCoBiXSlevIJ37e+FCb8gOSeCIhAyRDQ53HJHLU2KgIikGACG220kfWOSLr+/fsn2FO5JgIiIAIiUBUCEumqQk9z80Zg4cKFpqyszK5PF71OnTrl7VlaWAREQAREIDUBiXS6HSIgAiJQ8wQk0tX8GcgDERABEagOAhLpqoOynlEpAoMGDTKIdUOGDDENGzas1BqaJAIiIAIiUDUCEumqxk+zRUAERCAXBCTS5YKi1hABERCB5BOQSJf8M5KHIiACIiACIlBjBKoq0vGPLUuXLjVt2rQxtWrVqrF96MEiIAIiUNME/v33X/PJJ5+YRo0amfXXXz8rdyTSZYVLg0VABESgYAlIpCvYo5PjIiACIiACIpB/Ar5IN23atNhdBceOHWuuvfZa880331gnH374YbPTTjvl32E9QQREQAQSSuCJJ54w55xzjvVuww03NOeff77ZZ599YnkrkS4WJg0SAREQgYInIJGu4I9QGxABERABERCB/BGgmyDlB5o1axarWPny5cvNueeea0aPHl3OqRtvvNEceOCB+XNUKxccgZ9++sn6vNZaaxWc73I4eQTeeustc/zxx5v11lvPPP3006Z27dqJc/Kpp54yZ555Zjm/Dj/8cHPllVdmjDSWSJe445RDIiACIpAXAhLp8oJVi4qACIiACIhAaRK45pprzB133BFs/sgjjzR77LGH2WGHHSK/NC9YsMB8+eWXBnGPVDD+yx9spZVWsnPq1atnGjRoYFPE1lhjDftzOvvoo4/Mp59+aj7//HMzd+5c88cff5j69eubddZZx2y88came/fuaWudLlmyxMycOdPgG6m6rVu3NltttZWdn8p++OEHs2zZslgpbPPnzzdNmzbNuI9sbtA///xjxo8fb9ltvvnmVqiAWbbGOt9//71BQEOg/fXXX+2arEfkT2UFNdi899575ttvvzV//fWXPZMLL7zQuqcGUdmeksZHETjllFPMc889Z98aN26c2XLLLdOCmjVrllm8eLHp3LmzWXXVVasFKr9fr732mpk8ebIZMWJE8MyzzjqrgngXdkgiXbUckR4iAiIgAjVOQCJdjR+BHBABERABERCB4iDw+uuvm4MPPjjYzKhRo8x2222XcnOvvvqqOeKII7Le/A033GB69+5dYd4HH3xgEAmnTp2adk0Et2eeeabCGISjW2+91QwbNixyPhGCJ554YgWx8YorrjD33nuvnYNf+JfKSAFm/W222caMGTMm672nmnDffffZiEffENU6duxoRTtEUv6bytg7IsdLL72U1qdWrVpZcW233XaL5TsC3yOPPGJuvvlmK/xF2aGHHmoGDx4caz0NKkwCf//9txXvEdgPOeQQK5rn2vbff3+D8IYRsbb11lunfMSAAQMMn0/Y6quvbl588UUrRFenIdYddthhwSMz+SyRrjpPR88SAREQgZojIJGu5tjrySIgAiIgAiJQNARWrFhhDjjggOBLMnWXTjvttLT7i0r9igMkSgh74IEHzKWXXlphuov88gUivpR/+OGH5cYuWrTIHHvsseadd95J6wJCwG233VZuTIcOHcoJUM8//7zZbLPNIteh/hRiIjZnzpycRfCEIxijHo5oQcROVG1AUgV79eoVB78dQ4reVVddlXY8TPv162deeeWVtON23HHHclFFsZ3QwIIhMH36dCvOYQcddJAZMmRIzn3ffffdbQQtlu53kIjO/fbbr9zzzzvvPCtSV7ch6LvPk06dOtmo0lQ2fPhwQ41QPucoPyATAREQAREoTgIS6YrzXLUrERABERABEahWAh9//LHZc8897TMRwd58803733RG6hfRdAhopLXS/ZW0SKKviOiaOHGinU403qabbmrTMEm/vOCCC8qlsvnNLRi/8847W8GtrKzMrLLKKnYNRETSTOfNm2cjZsIi2jHHHFMuiuz00083e+21l/nzzz/Ngw8+aGtcOSMiaO+99w5+5su1a5DBi6T4El0XZUcddZSZMmWKfev9999Pm3abzQEOHTrUXHfddXYKKb3/8z//kzKiEJGTiL6VV145eARnsckmmwQ/U9AeTqQXcybsDwHBCYwMJDquZ8+ekW7+9ttv5j//+U+58YgovEYaLSKNY4Z4iGArK14C3HnuPpbrKFJHDbGX1HkMYbh58+aRQL/44gv7GeEbgjPCc3UbqfV+Wm46v6vbNz1PBERABESgZghIpKsZ7npqDAKkIvAXef6VsWHDhjFmaIgIiIAIiEBNEfAj2YjIuummm6rkyj333GOLqWN33313IABGLepH0Bx99NE20oR6dnEtnHaGwIbQ5gyB7+KLLw6ivRCvEAad7brrrlb8842adtSdCxuRZXS+xd59913TuHHjuG6mHUf3XHzEENhOPvlkg1BGjS5ERl9cY8xxxx1nLrnkknJrunQ6XkR0XW211So800/tDXPwB/ft29e88MILwUucpZ/a/PjjjxuilzBScR977LGccNAiySTgR2rmS6TzxfIZM2aYddddNyUMRHiX8k4K95NPPlljf9c84YQTgn+QQDz3SwYk8zTllQiIgAiIQD4JSKTLJ12tXWkCpCERwYCpoHSlMWqiCIiACFQbAV+Uoa4bqa9VsbvuustcffXVdonbb7+9QnqaWzsciVIZ4ctPFSU9ltp64ULyPIcC8whf2LRp04KUMxpR0KzCt5NOOslG/IXtoosuCsS+t99+u9KNGMLrIvwhAGJRReiJWOR9P+33+uuvt5FtGNGLROA5o+FGVHdMmntsscUWAQfElyZNmpRzJyx6Ih7SddM30op79OhhXyICsE+fPlW5LrHmEhVZp06drATcWAtnOQjRl6jRUjJ+P/g9wTKldVaWi592HudzAOGaxjDbbrttpTvB5uJO8fdc6l1i++67ryEqViYCIiACIlC6BCTSle7ZJ3rnfuqSRLpEH5WcEwEREIHgi7dLX0xXDyouLlJKEc+wG2+80Rx44IGRU0mrpcaVM35ee+214z7GjkMgcpFxAwcONAiOUXbqqaeaZ5991r5FHSnq02Euko4UWl+se+ONNyp0hGV9ItuwXIp0dIskOg5L1SkSofGMM84I0m39BhqIby1atAi2TWpwKvM50BSiS5cuwVAEKFJgXW2/qIg9NxghhfRlf35WBxdjMILhhAkTDJFVrl4Z6dMIRkRd+im/bjlSf0m3ppsvjNIZoi0MaMpBenWUwYR0aXxhz/iBIEp9QviQUhxlNFsgApE7RXbB9ttvHwyjczG11VwnXoSvXXbZJQaRqg2hziCpq/y+0BmVn50PiPNEtYaNFFQiM51QC38ib2GfjWgKR86R33H2TqQnd5ZUeJ5L2rQT0fnH3nC6PXec97lzsOVnxFLqu0UJ0qlIVeZOpaPuC9ZE9fkRqFU7Lc0WAREQAREoRAIS6Qrx1ErAZ4l0JXDI2qIIiEBBEFi4cKEVsfgim6qoOV94+XLpLFWqZDYb9iPpiKjzuyD663z99dc2ws0ZAsAtt9xi1l9//ViPC9di48t/o0aNIuf6wqEvhLlaWKRtUgfr0UcftfMRgcIdV/100VyKdH70GhFz/fv3j9wDZSQQdJyY4e/XT3dNJ9KxNumBWLgjpV97jPfjRDTFOqgsBxEZiGhE3bxUBgfGIMb5RuQf6cPY6NGjbaRVKvPTJqPOk/tJ+nGq5hkISaT6RomBCHuIqhiCHhFWvMb9DqdXsw41DqNExyzRRQ7/7LPPzGWXXZa2czIioROg3SJElCKSZjL8J4qVLsX+Z4mbhyBItNmkSZMil2KuHyUajgTlZ2oxRnUYRjBlXVe/MpWvVblT6fbP3tq3bx8MQYDNJl0/E1u9LwIiIAIiUFgEJNIV1nmVjLcS6UrmqLVRERCBhBPwP4/5st22bdsKHhMpg1DlLJ3AE3e79957b9B8IV10G+tRPy4sgiDA8GUf0axjx47W73AKK3OJanLRP3zRR2hJZYhvLoWVqCBXA86JdNTaQlDs1q1bsARdLWni4Iz3ESCxXIp0fvdMas25qLrwXohGgocTK/y03bginZ/e64t8RCbRNdPVv0PAIgKsJswXQ3k+Z9SmTRsze/ZsAytnnBX1D33zO/CmSz/89ttvy0W3hc8aIZTn+sIQpTyIaPR94NlRDQOoxeg66CI+EzmWrlMuAqkfDZkr7nwG0IjFCbv+uohr/uuIh75QGFWvMZ1fRM+6LrBu3B9//GGjVf3mLJn2RnMIP6V43LhxabtNx4n+rcqdSudvOIo1KgI30371vgiIgAiIQPEQkEhXPGdZVDuRSFdUx6nNiIAIFDCBOJ/HCB+u2+mGG26YNtomLoqHHnooaGxw4YUXmhNPPDHlVKKVEOpcOmOqgUQ0Ia75qW0Ij0T7YJlqZRE1duaZZ9qxhx56qBk8eHAwDwHBpY/6HVyp+UbtN2d+/btcinTUnHONGVJ1Xf3555/NsGHDApEw3PjBiXQIL6QLRhkiDIIJFhY1ieRC1HKWy/3FvTeMI/rTTz1FWHVnzPujRo0qJx4SneZHMpFi6gt3qaIrfRENltQy9IUh/6wRjBGeXcdRUlhJ4XYCF8IgZ+Mb94Z6jGGDO/eqdevWQR1CxoSjGrNhlmosnX1btmwZvM3dIN15t912syI4Nd18duEahaSm0rzkk08+CYRJPiMQtIlM4w/CMUIVaeqnnXZahXR1UstpIuaMiFU+D4iARJhEPHddXd2Y8D8UwJkoPVJziZgjUo15jj+RdPBMZVW9U5nOwq+nR6q132k501y9LwIiIAIiUFwEJNIV13kWzW7ifCksms1qIyIgAiKQYAJxPo/9unC5qqk0YsQIQ5MFjDQ3hIF0RrQNX7r5su13Xg3PoW4VNcRcvSrSNl1qKGm9NDFIZX5zBlLnnHDgukqyNkIJog4RZc78KB3mIDpguRSxXnzxRRvthCHWUSMNUY4oLoQJBLRwiiR86SzpjGhDRItUIh3rIIa6unuui6ybP3z4cHP55ZfbHxFx7r///hq52X5zDuoEwj9siLUudTIcLUdqZ9euXYMpfoMN9yLCEnt0TMN1AMPRpePHj7dn4s/n3rlOv6Rcvvzyy+Xc9NNu3RtE4hGNueaaa9qX/M7G+RDpiOrirjubOnWqQWTzzU9pJYqyQYMGFXiT0st9cffTdW7OdEH++usvW3POGcwRR/3UVOriIVr6In2caF4/YjJqX75vVb1Tmfbpd6al7mW7du0qTKFjNp9tQ4YMCZrWZFpX74uACIiACBQeAYl0hXdmJeFxnC+FJQFCmxQBERCBGiYQ5/PYj+Ki8yeRM1U1/0s9KZOkTsY1onNIRaQeGmlu4ZpYRMMhqmB+Z8WoGnL+MxH3iOrDfEHPRcEQHTRmzBj7/imnnBJw2HnnnQ2RgRhNMKgphkWJdETRkIKKWMY+iDAimonaefyhPlq4UyprIQKdfPLJcRFZgdEXX5joR/MQwUUEFYIddezwlUgvl3KIUEOBez+F2Be+8MWJMrGdytFAl37McqlSpSdOnBgIlFEC2eGHHx5EhJJqSvSdb36xf14Pp7o+88wzwZ3dc889rbCEcaacL/UN/ZRXRGjX4dM9x2/QwWucF4KhH63nxCOi66hLWK9evRxR/N9l/N9/fub3EFET4czVTUMMfvzxx82WW25piHKLMu7Otddea98iCs79HmVyds6cOWaPPfYIhiFk+l2I3RvcS4QuLF0kqP88PxV35syZpmnTpindycWdSrdX35dUdRBdpGu6mpOZeOp9ERABERCB5BOQSJf8MypJD+N8KSxJMNq0CIiACFQzgTifx6T5HXzwwdazXEXS+eLZOeeck7aeVCYkiHWIC35KnOv+6KfVputEyjNIgXQRQMccc4wtpI+5CDQ/XTYcjeW6oPopjOE0SqKzXDpkuj2Fi+IzFmEUYTDKEDUQ3BBWEPkQnaLEHF+kS/d8BCGi5ogcTCV6pOvIm+m8qvJ+uBEIkZLU4AvbrFmzgu68vBeuYUaUnS+GIoBtsMEGwTIIkAjJ2AEHHGAbUPjmi7GIzHBHYCK1NlxbDWGLqMO6deuWW8NPm0b8JlIu3Nzg999/t0IaAlmTJk2qgi5yLjxZO1yPDiGMlGLu/E477RTZ7MFf0E/9JYIQoSmO+WJqus8Wv3lNXJHOj15LFQGIj7m6U+n26/uSKiJSIl2cG6MxIiACIlD4BCTSFf4ZFuUO+Fd7F+rPFzX3r6NFuVltSgREQAQSTCCOSOdHFWVqvuBvlS+/pMoiHjHPtyeeeMIgzmGk/UVFj2WDDaEOMcWZSz/0UzT9OnNRa/tCA103zz77bDvMiXSILU644XUio1xHXNIuSWMjgo0oKoy00bBYtv/++xsEpChDfCCtz4mD/hhfzAjPReBBXAyLauFxfrRQKrakG7KH8Hn5HPjf+Ui9jHPe4TTTGTNmmHXXXbfC1HCNsbBgyt1EzHRNH/x01nDDCARSGPvmRxWm8huG1Mvr1atXZFdWatYR4YURiUdEXk0Yv9/46dKco3yAFb8Pqf6+xp116c/hNOt0e/IjEqOafLi5iJX8jmFxP4N8UTpdR+pc3alU+0ScJxXaCaGpmlhIpKuJ269nioAIiED1E5BIV/3M9cSYBPjCwV+i+/btG3OGhomACIiACOSaQByRjsYNnTt3Dh4dt9aa++IeFSHz8MMPB91T6apILbSqmv+lHMEAwclPYc1UR40IICKzsEsvvTSoAee+PO+yyy7mwQcfDNwMc6HeHVFwrrsr0XbhyCjSWxcsWGCbW9SpU8d29CTCym92EcXBr0lHtB7ijhMI3Xj+/xSxJfxM976fckdkGALVn3/+adMH6RqKkBAlzjGfNE4/DTFKuKrq+cWZ73frZXy4kYFbI5zG6SIr/WcgpiLMYjBArCK91+/QGz5zN98X2MJ+02CE+oHUl4vqOOzG+110w80t4rDI9RgaxBBRSP02/kQZaa3UegubX9Mtm99n/x8A/HTy8PoIXK7zdNxIOieusxY1Gxs2bBi5p1zeqagHfPXVV+XShFN9fkqky/WN1noiIAIikEwCEumSeS7ySgREQAREQAQSQSCOSBeOBKE+lS/apdpIuppQfg0rxBLXPbayUGgs0aZNm2A6dfT40kt9MCLosHC30/Cz/CL9iHEINJj78uzXHnNzKfZOt1UM8QBhhppTWDjFsrJ7Yx5dLkmPxBDYiBpEeCDiz28YgdABWzpjhs0XhVJ1NE3lYzhVl7p7PXr0qMqWKjXXj6hiAZdmHF4M/0hJxVJFXi1ZssSmejrjHKkv6EckpqofBneENWfcLWrKESmJKB3H4tQpi7NOPsbQ0IEUUSJSiR51UWCpujsjDtPYBaM2nUuPz+QbQjHiuvv94V5GCdbh3+84jSN80T5dTbpc3qmo/VKHkvT5dHeR9yTSZbotel8EREAEioOARLriOEftQgREQAREQATyQsAX6dJFmxDp9sorr1gf4qanEtlF8wEsHF1DwX8XlUbzB18s8TdKtBpf3BE00kUl+WlzfqRNONotVWF6ivwfcsghwaOJ8KHDpl+vKqo2GeIFaaQubdL3PY6QEPdQfZGODqtOsFu6dKlNQyQ63RmiFBGB4fp3frdLxMtmzZrFfbwd50ePRTVbCC+GSEnUEOKm67ab1QNTDPbre4U70LopCGZ0LsXSpVH6NQRJaaWJAcIrlm6P/jz2d+eddwaNFny3uT/8DlBPDgHVt1SicC4YxV2DaE+iEbnD66+/fuQ0mmpQd88ZkWdEgfpG5OkDDzxgX2j08n0AACAASURBVMpU+zH8ED/iLVWkXtiHqFTy8Lq+SJfpvufyToX9oNuz6xQdJfS78RLp4t5ajRMBERCBwiYgka6wz0/ei4AIiIAIiEDeCSDwNGrUKG19UF+UoDYUdZUymR9BgkhDHTPq02G+4JMq/QsBytUCQ+CgsQPCWdgQY/xOptQAc0ILY4n4QnTDEBsRDH1DyDvssMOCiDTWcl+qSQdt3bq1He6/7s8PCwi8FzclLxND977P8rTTTgvq+fE+UW4IAUOGDAmWQ6iDN5FPznyRLlVdrHT+UPeOM3DGM4kcC9vixYttdKETbRARiTzLlfl+cC9I+/Wjr/zoLJ6ZrjHJDz/8UEE8c36Skk3ThChDWOYc3FkTqRWuP/jrr7/aZh9O3KZZhbtLzKODMCI5loplrphFreNHkBEJSGRgOAJz0aJFtl6kq52XKmXcb9DC3Uf4I5U7jg0dOtSQKo5xb6lXSSMUZ+FOu7xO+rc/Juo5fg3GTONzead8X/jd5A65pjbpOllLpItzWzRGBERABAqfgES6wj9D7UAEREAEREAEapyAH8mFMzRJcA2A0jlH11Wi3JyYQdoXwhFNF9yXckS6TCIC7zMPga19+/ZWECGih2g8vzYbYgMper6YF/adJgFEtFArirRYRDa/uyX+UlcM82thEWnnapj5/lKvDbGK9EBnmVJrsz1QP1LwoIMOKifIubUQxYhocobAifDiBCxfpCM1ke6d2dh3331no8t8u/DCCw1ptKRHUveNaEw/PZKxCJ6+iJrNM6PGhhs7cJYnnHCCbSxA9B53y50FghFRVI0bN075WL9hiBvEWhMmTDC1atWKnEeEXJcuXYJOrkRZEuG4xhprGFIzJ0+ebBC2/Y7DvOZEahb1fzeyqeNWVX5uPgKcn9pLqvbtt99u7wtCK0IkYqsfJUq9Rc47bIhyiOPOSBs++uijbYQezcJoIEO9O0TVcJo0vIiUdV1xOTPOlEjQOXPm2M+asIX9IOUbsZ2aj87oMOt8h68fWUr0nt8tN9d3yvnAvvl9dYYAuf3220ceoUS6XN1srSMCIiACySYgkS7Z5yPvREAEREAERKAgCPDlt2vXrkG0WVTqZ9RG+LLPl3e/bpo/jigd0mdTGRE2RNrEtagIMaJZTj31VEOzg0wWjvrya2EdccQRtotqlIUbFSCQxXleJn/c+34DDAQQIpeizI9o4n2/Pphfky5VWmEmf/xuuZnG8j7iJVGNmRpjxFnLH+NHX6Wbe8kll9j0y3QWFqsYG4cPKcU0G/GNSLCo1Oeoe+43qEBQCq+VLZPKjA93G0Yg8wVrf03S1/ldXWmllSo8it+xE088sVzadZQ/qSJMiYZF1Ev1bObRYMWx9VPu/aYqcRkgThJpmq875dZFPHap6Jk+E3if6GFKAaipWtyT1DgREAERKDwCEukK78zksQiIgAiIgAgkkkA4rTOOkMFGiKQhNdCl/fmbC6cAhjdOxBL1vohKSmcIaEQmRTVMYB7RbldddZVBZEpl5513nk1PDJtLm8vULIEoQdJSscMPP9w+L1eG4Od8o5ZZun34wiaRUD179rRuUMeOqEIsVURUHH/HjBljiEZMZ4gqdPykgcDKK68cZ9msx/gdgqMmw+E///lPymg4fw7NOFy6MBGb1C6MIyyOHTvWILCls8GDBwfNS/xx/lxEZBddmjWIKkwglZRU71TiGEtzlmeeeaYV4dIZjThIa3Z3LGpsunp1RGqSmhz+nEC84iyJ1kN0xYjW3GGHHez/9n834qJgLmuELZd3Kvx7kunzEqGfDrtEnabqRBt3fxonAiIgAiKQXAIS6ZJ7NvJMBERABERABAqKACmNRHH5aWl8aSada5VVVkm7F8Q2BDnSS/kvNfAQxaJS56IW4gs8KZ+kU/J86l2ROkhdKoq+h5skpHKGQvnuyzARQaS8bbzxxgbhK1VzA6J3SFv0UwOj1kfoIKWPBhektMWtyRXnEvz999828oc6Z6StphIj3VowJgqQSCmXskl6LymMiFBwj4qIiuMLY4iMRMhCOHFF/GHJ2qSB8ieXzSJS+UVzDs6TtEJqrLVo0cKeJ92HUzVCiFqLuYh0nDMRXdmkAsOCc0fwWrhwoU155c/mm29uo0832GCDSPc5H4Qb7g3P9OsHxj2HXIwj1ZMIVKLZnMAGR36n+H3fd999K9TbS/dcfsdJMeZeLFu2zDRo0MDW4uP3NA5XxD5+z7nzNH+ApTP4cm/9s+VzibRu/jEAYZX3EYbd/+a//Oxe4/eTtO1wDUH3jKreKfwhBd8JiqybjfCbizPVGiIgAiIgAsklIJEuuWdT8p5RMJm/bPEXmWw7zJU8PAEQAREQgRoigCCBKOen9CHGIKBlKuReQy7rsSIgAiJQLQSiIhOjmrhUizN6iAiIgAiIQCIJSKRL5LHIKYpLU6AYQ6TjX1dlIiACIiAChUFg7ty5NiXLF+pIRyW1UCYCIiACpUpgxIgRNs3bGQIdtQvjRvqWKjftWwREQARKiYBEulI67QLaq19gWyJdAR2cXBUBERCB/yNA+urMmTNtetyff/5pa5SpjpKuhwiIQCkTIFWXtOn69evbjrWkyMepbVjKzLR3ERABESg1AhLpSu3EC2S/EukK5KDkpgiIQNEToOwAkc2UHZgwYULR71cbFAEREAEREAEREAEREIGaIiCRrqbI67lpCUik0wURAREQgWQQ8D+PEenatm2bDMfkhQiIgAiIgAiIgAiIgAgUGQGJdEV2oMWyHYl0xXKS2ocIiEChE9DncaGfoPwXAREQAREQAREQAREoFAIS6QrlpErMT30pLLED13ZFQAQSS0Cfx4k9GjkmAiKQEAI33XSTadq0qenVq5epV69eXrwaNGiQmTRpkrnnnnsU0ZwXwlpUBERABJJBQCJdMs5BXoQI6EuhroQIiIAIJIOAPo+TcQ7yQgREIJkE/M9IPKSGJ2Jdt27dcurwRhttZNfr16+f6d+/f07X1mIiIAIiIALJISCRLjlnIU88AvpSqOsgAiIgAskgoM/jZJyDvBABEUgugZdfftlMnDjRPP/882bx4sXWUTq4Itb17NnTdOjQocrOS6SrMkItIAIiIAIFQUAiXUEcU+k5+csvv5h27drZjY8cOdJ06tSp9CBoxyIgAiKQAAIS6RJwCHJBBESgIAgsWrTICnUIdlOmTAl83njjja1gR5Rdy5YtK7UXiXSVwqZJIiACIlBwBCTSFdyRlY7D/AVn4cKFpm/fvqWzae1UBERABBJGQCJdwg5E7oiACBQEgY8++sjQEZu/z3788ceBz/zD8wEHHGB23313s/baa8fei0S62Kg0UAREQAQKmoBEuoI+PjkvAiIgAiIgAvklIJEuv3y1ugiIQPETIB0WwY4ouyVLlgQb3m+//Uz37t2tYFe3bt20ICTSFf890Q5FQAREAAIS6XQPREAEREAEREAEUhLwRbr333/fNGzYULREQAREQAQqQeDvv/82Y8aMMePHjzevvvpqsELjxo0Ngt0ee+xhdtppp8iVJdJVArimiIAIiEABEpBIV4CHJpdFQAREQAREoDoJjBo1ymywwQaqD1qd0PUsERCBoibw5ZdfBoLdnDlzgr22bt3ainX8ad++ffC6RLqivg7anAiIgAgEBCTS6TKIgAiIgAiIgAiIgAiIgAiIQA0RePPNN61g9+yzz5qlS5cGXmy33XZWrCMddtddd7Wv9+vXz/Tv37+GPNVjRUAEREAE8k1AIl2+CWt9ERABERABESgSAs8995w55ZRTimQ32oYIiIAIFA6BOnXqGNJlBw4cqKZqhXNs8lQEREAEsiYgkS5rZJogAiIgAiIgAqVJQCJdaZ67di0CIlDzBHr06GGaN29uBTrVBq3585AHIiACIpAvAhLp8kVW64qACIiACIiACIiACIiACIhABgITJ040Y8eONfz333//DUb76a4bb7yxOIqACIiACJQAAYl0JXDIhbrFm2++2SxcuNCG9etfDAv1FOW3CIiACIiACIiACIhAmMAbb7xhhblJkyaZH3/8MXg7VeMIERQBERABESgNAhLpSuOcC26XiHNlZWXW75EjR6qjYMGdoBwWAREQAREQAREQARHwCdDF9emnnzaTJ082n3zySfBW48aNzX777WebROy0006CJgIiIAIiUMIEJNKV8OEneev//e9/TZ8+fSTSJfmQ5JsIiIAIiIAIiIAIiEBaAj/88IMZN26cjZh7/fXXy41FmOvevbvt3lq3bl2RFAEREAEREAEjkU6XIJEEJNIl8ljklAiIQAkS+OWXX8yAAQNMs2bNbPkBmQiIgAiIQHoCy5YtMzTaIWIOcY6urM46depkDjjgACvMrb322kIpAiIgAiIgAuUISKTThUgkAYl0iTwWOSUCIlCCBPzP42nTplmxTiYCIiACIlCRwNSpU60ohzj3zTffBANo+tCrVy+z1157mZYtWwqdCIiACIiACKQkIJFOlyORBCTSJfJY5JQIiEAJEtDncQkeurYsAiKQFQGanSHOzZ49O5hXv359K8z17NnTdOjQIav1NFgEREAERKB0CUikK92zT/TO9aUw0ccj50RABEqIgD6PS+iwtVUREIGsCfifkUwmWg5xrlu3blmvlW7CqFGjzIwZM0y/fv0U0ZxTslpMBERABJJFQCJdss5D3vwfAX0p1FUQAREQgWQQ0OdxMs5BXoiACCSXAJF0TZo0seJcvXr18uJou3btDDVCqQ3at2/fvDxDi4qACIiACNQ8AYl0NX8G8iCCgL4U6lqIgAiIQDII6PM4GecgL0RABEqbwEYbbWQBEEnXv3//0oah3YuACIhAEROQSFfEh1vIW1u4cKEpKyuzWxg5cqShE5ZMBERABESg+glIpKt+5nqiCIiACIQJSKTTnRABERCB0iAgka40zrkgd3n22WfbsP4hQ4aYhg0bFuQe5LQIiIAIFDoBiXSFfoLyXwREoBgISKQrhlPUHkRABEQgMwGJdJkZaYQIiIAIiIAIlCwBiXQle/TauAiIQIIISKRL0GHIFREQARHIIwGJdHmEq6VFQAREQAREoNAJ+CLdtGnT1FWw0A9U/ouACBQkAYl0BXlscloEREAEsiYgkS5rZJogAiIgAiIgAqVDgLIDgwYNsuKcipWXzrlrpyIgAskiIJEuWechb0RABEQgXwQk0uWLrNYVAREQAREQAREQgQIjMHPmTDNhwgTz119/mb///tv8+eef5o8//jC1atUyxxxzjOncuXOB7aj43X344YfN4MGDTe/eva2gLitOAhLpivNctSsREAERCBOQSKc7IQIiIAIiIAIiIAJVIPDGG2+Yzz77zDRt2tQ0aNDA1K1b16y66qr2zyqrrGJWXnllU7t2bfvflVZayf5ZffXV7WtJsx133NF8+eWXkW7RaZ2O67LkEPj333/NFltsYX777Tfr1BdffGEFVVnxEZBIV3xnqh2JgAiIQBQBiXS6FyIgAiIgAiIgAiJQSQI//fST6dChQ9az11prLTNp0iTTpEmTrOfmc8Kpp55qnn322chH7LPPPmbYsGH5fHzi1n7yySfN3LlzzYEHHmg23njjxPmHONe2bdvAr/nz5+fFx3feecc8/fTTZs8991Q0ZV4IZ150+PDhhhqhl156qWqDZsalESIgAiJQsAQk0hXs0clxERABERABERCBmiaASLLtttsGkUzZ+IMA1LFjx2ymVMtYorGI0CIi65lnnjE33nijfW6fPn3MddddVy0+JOEhpPm2adPGukLk4+zZsxMXpeaLxPj44Ycf5gUdIiWp0NgLL7xgWrVqlZfnaFEREAEREAERKHUCEulK/QYkeP8333yzWbhwoRk4cKBp2LBhgj2VayIgAiIgAqVMYOnSpeb99983P/74o6HRxu+//25efvllM3369EDg2WuvvWx9N/7wfrt27cy5556byJRX/yxJb8VP7KijjjKXX355yRx1OErt448/Nquttlqi9v/NN98Y0pAxojPffvvtvPi3//77m1mzZtm1H3nkEdOlS5e8PEeLioAIiIAIiECpE5BIV+o3IKH7R5wrKyuz3vEFwf0FNKHuyi0REAEREAERKEfgzjvvtMX8sX333dcMHTq0IAmNGDHCXHTRRdb3E0880Vx44YUFuY/KOE00YYsWLYKpSRTpFixYEAhmG264oZk6dWpltppxzuGHHx6sLZEuIy4NEAEREAEREIFKE5BIV2l0mphPAtTcIK1GIl0+KWttERABERCBfBG49957zRVXXGGXp47X3XffXalHEXlXp04d22yiskbkXr169So1/cEHH7QR7diZZ55pzjrrrEqtE3fSihUrzOLFi82aa64Zd0pW41g/m8YKrlg/D6E2XdKafXz++edml112sQw222wz8/zzz2fFI+7gE044wUycONEOf+KJJ8z2228fd6rGiYAIiIAIiIAIZEFAIl0WsDS0+ghIpKs+1nqSCIiACKQjQPrmgAEDbNmBG264QbBiEnjooYfMJZdcYkd369bN3HPPPTFnGvPaa6+ZCRMmmBkzZphPP/3Uzttuu+1M9+7dzdFHH227xKYzIsAQUqZNm2befPNNQ0okqZBbbbWVOeKII8xuu+0W2xf8vvLKK+147sHpp58ee262A//55x9zwAEHmA8++MA+85BDDjFjx441dM+lcy7PR6xcsmSJ3d8nn3xiG2/weirxDFGOhgcwfffddy1PGkDQBOO4444za6yxRqSb33//va0z6AQwBr333ntWMKVjb7ZiHenQY8aMsV2AqRuH+IrQRU3Cww47zDRu3DglLmrjESH31ltvmTlz5lgWzZs3N+3bt7f732OPPexczpcagqnsu+++M0RGEhHIH7r4brPNNramYo8ePYL6e/58fv9J40aodVF6CLfcR1hky6EyPmR7jzReBERABERABAqZgES6Qj69IvZdIl0RH662JgIiUFAE/M9jRJ9mzZoVlP815SwpgS41FKEHYSOTLV++3Nx6662GmqypjPIPjFlnnXUihyBgEe1Gcf9UhtBHCisiSya74447zDXXXGOHnXfeeeaUU07JNKXS7yOkIVhhiGiIdi56i9eIRmzdurXZe++9yzXq4HWiFcP29ddfm/PPP9+88sorkT7RaOGxxx6z4pZvvsCabjPMr1u3rhk0aJDZb7/9Up7HkCFD0p4/aap07tx0000rrPHRRx9Z5vPmzUu5B8REjLtBiZCwwZH76CIiU+3prrvuskKwM0TJVPsKrwELRFUnTOfKh0pfJk0UAREQAREQgQIlIJGuQA+u2N2WSFfsJ6z9iYAIFAoBfR5X7qRGjRplI7ywHXbYwYpBmYz0WNJkne244442uomuoq4JBe+lisxD5EPcQthxRj08Iq8QwFxUHu8hLCHWZbLbbrstiKC8+OKLzfHHH59pSqXfHz9+vDn55JNTzkeEIsItLFj169fP9O/fv9w8hCv40f3UGc07EDF9lryHiEdkmrPLLrvM3H///bH3QfQfwmnYOA8aLhAZGMfCNe84R180y7TGzjvvbBAYw0ZUYtxITr/jMKmz1CGMa+m6y1bWh7jP1jgREAEREAERKBYCEumK5SSLbB/6UlhkB6rtiIAIFCwBfR5X7uhIsTzjjDPsZFIKSXVMZ37DJMZdcMEF5qSTTgqm+KIfL7I+6Y6+kerop6P6tcOIprr00kttuiOGoEIqLP9NZ0T13XTTTXYI84899tjKAYkxK+w/U2hYQJqqL3QReda1a9dASIsSyYj+IwoQa9WqlRU/nRCH+HXggQcG0XgIm8OGDQs8RASE06JFi2y6rbODDjrIILy5P6QV0+2Vrrfhs2DOo48+as/RGfcAsQrhlTRS/HM+MgYR1Y9uJDLNFxR5DnslhRcBjfVdFB3zd999dxuR5xvCnx9lSNrzjTfeaJtz4T9p1dQadPb444+bzp072x9//fVXQ3Tdzz//XE78Yz3uDXcKFqxDGjKCIqJk2KriQ4xrUzJDOFtS4ImIVERzyRy7NioCIlCCBCTSleChF8KW9aWwEE5JPoqACJQCAX0eV+6UET+cyJapVhhPIP3UCWipGgAQxTZp0iTrULhjLEIJkVTUGcOotxZOPaQOWocOHQJh56qrrrIiWDpD0LnlllvskMsvv9wKUvkyBDGi4pz16tXLCoQ8Hz+cvfzyy7b5g6sXF+YLA6LonBGht/nmmwc/I3IReecEOGrUsWbYqB+HGIhl2zmVCD58cCIadQARCv16gr4wG45Co/4c+3d27rnnmlNPPbWci4iXiHbOiBSkq7Az9vmf//zH1vTDEOheeumlCnX4iFCkbiEGB3iErW3btsFeEIrWXXfdWNcglz7EemARD3JNTKIiR4t429qaCIiACJQcAYl0JXfkhbFhfSksjHOSlyIgAsVPQJ/HlTvjF198MYg6i9N1E0HHCWxEyvTt27fCg6nPRpdNLCwsffvtt+U6bj777LOmXbt2FdZAaHPRVsccc4whtTOd0SyElFeMdNwjjzyyckBizCLa0O8ei7hE7T2Ep8GDB9sVEJ2uv/564+83zMKPyPM76xL1RV1Fotf8CDXEL0SwsPlCWZwz9OeH69qRbrzBBhuUewTRgUTxYWGh0a9puN5669mmDTSsCJu/V6LY3FkxLpwuS7Sge56/jt/BlqYW4ehKuPnCHbXqGjVqFONEc+dDrIcV+SCJdEV+wNqeCIiACPwfAYl0ugqJJOD/6zJFkPlXXpkIiIAIiED1E5BIVznmr776qu2kiqWK1HIrkza4ySabBA/y64L5T581a1a5dMIvvvjCRpRhpK6Sjuls7ty5kZ03/W6tUemR4d1ed911ZujQofblfIt0fkqvLyD6PlPbjxp/RKoRFYiFo9z86D/qAtK9lAgxUoRdxJjbJ2tRf44GEGEj6gw/sDgpy/58hD+EUiwc9ejG+Y0yiLTz6+D5YmpUVKRb4/XXXzcHH3yw/bFnz57lmo4QmUmEJpaqXhydY0m/dTZ//vwKHEjN9QVfOsyuuuqqsX4xcuVDrIcV+SCJdEV+wNqeCIiACPwfAYl0ugqJJcC/9CPWkZLSsGHDxPopx0RABESgmAlIpKvc6ZISSNQXRiQUHFNZOD0zVTphuG6dH9GEsOeaJ6RLzfRTSrfYYgvz3HPPpd2gX9stbrOJyhEztm6fi6Tjv65Wmh9JR4RZly5d0op0flpwKl9I/aReHCmlfgqqP95vnBC3Q6+bv+uuuwYNLs4+++ygPqG/vi8Chuvi+enPqSIrWcsXg3v37h00+eA9agg+8MAD9pGpOr/SSGPLLbe0Y1IJeT/++KPp2LFj4HqUkJeKc658qOydKqZ5EumK6TS1FxEQARFITUAinW6HCIiACIiACIhASgIS6Sp3Od555x3To0cPOxlB6O233065EA0DiGpzRpplkyZNKoz3z4I3/dREv0lBusg9v75bnFp51157bdBUgRp3RHXly5566qlAmPNTUP3mFU6k++6778x2221nXQnvl6YQM2fOjHSTPdP8gvptmaLB/FTSsIiWiYFfww3/iXILmy8ChlNVfWESsdJPA/bXmTJlSlAnMLwGtctc3b0+ffoYoiLD5gtwqUS6r7/+Omgmka6DaxSTXPmQiXcpvC+RrhROWXsUAREQAWMk0ukWiIAIiIAIiIAIpCTgC0Pvv/++Iptj3hW/HlgmYeP333831Dxz5oSo8KN8gS0s/Pmpk2EBz1+HaCvXSCAceRW1Nb8mHdFdriZeTAxZDRs3bpw57bTT7Bw/xfPqq6+2XUYxou1IPfWFI7q3vvDCC8Gz6KpLaqszIhnZKyIWY+Oa36E3qoNsunX8Om8IboiCYfOj5ahJ6BqHMM6vPxhuCOGv4597ONqPVF2i9bCjjz7aEAkZtnBH3ag06aqIdLnyIe6ZFfM4iXTFfLramwiIgAj8fwIS6XQbREAEREAEREAE0hKg/ECzZs0MRfhl8Qj4nUGZkSlF0O+wef7555uTTz65woN8ga1bt26GWm3OFixYYNNAnUXVtQvXHyMVkaiydEZ3VSLBsFR+xSOSeZTfEZcustRlwy6++GLz8MMP2/9Nei5puv5+w00daCxx++232/HcWUSylVZaqYID1AJE3CNqEeEvbL4/2TaO8M/z9NNPN9TG8+3zzz8PutPyelhoDEdXUntu/fXXr+Aj61LLD9t6660N0YjOaIZBXd+o93iNbr8IgPPmzQvmEPGJAOzbDz/8UI5PqkjPqBPOlQ+Zb0/xj5BIV/xnrB2KgAiIAAQk0ukeiIAIiIAIiIAIiECOCSB8UJfMWSaR7sorrwxENwQjxJXatWsH8/1GCbx4zjnnBFFn/LxixQoruBDBhyHyIar55nec5fXRo0fbpgrpjG6hRNNhCEIITvkyv0bbIYccYqiHh/mRceyhZcuWthMu0WdYWEDzI/KIYiT1tV69euXc/vXXX80pp5xiXnnlFfv6pEmTTOvWrcuNCXdHJbKuffv2sbZ/0kknGUQ+jEg+0lJdc4rffvvN1iuku6tv3Bm/Pt7hhx9uu7piNLi4++67TYMGDYIp4Q6y4YjN8PsIki6SkPtCrTvG+BbVFZixm2++ucFvDNGUun9xLFc+xHlWsY+RSFfsJ6z9iYAIiMD/EpBIp5sgAiIgAiIgAiIgAjkmQNogHTudETkVFc3l3v/222/N9ttvH4wnAozUUgQourgSkeREHcSYadOmmcaNG5fz2q9xxhsIatRSo5EE3V8RpZzQQj03F4HlFnniiSesaEWEFbbKKqvY1FgEQox6bghjderUsQIi/yVizO/8WRWMfmo1DR2I4sP8lEnSOzfYYAPbWKqsrMy+H65JR4QcUYWukyupqkTlrbHGGoZowsmTJxui7RD6nPHapptuWs79ZcuWWUHQGc9BfIMpRvo3vBDWEE198xs68Do+cIakjiKOOTHVn8NazZs3Bi0nrAAAIABJREFUD1765JNPDBGTzhD7+JlmWjQXcWnL/hp+lFu44QMCHaIr/hJp6KcEuzUQZInYDNuRRx4ZCJrcPzjQTXjNNdc03G1ESP5LCm+jRo2C6bn0oSp3qxjmEkG6dOlSe3/69u1bDFvSHkRABERABCIISKTTtRABERABERABERCBHBMICyxz5szJ2Khg6NChkcX9w66lauCwfPlyK2i56LB0WwpHhYVTYePiyNS5Nu46jKNb7X777Wen+DXgfJEO8YuIIl/UjOpm63e7dT6QxukER98vosKIDosyuqOSFpzJoiLxfL+j5lNDDnHLGenLvijH6w8++KAVZVIZwqGfrkqNOcRUf02iNFMZ5wcXJwD7tQD9ObNmzbI1/TLZVVddZYgA9I195cKHTM8u9vcR1RGy6eJM+QGZCIiACIhAcRKQSFec56pdiYAIiIAIiIAI1CCBX375JYgwI2qNKLVatWpl9Ijaa6kEIybToZNUyVRrEf1FmiuprFGGoEWEWlQNtu7du0dGeKVzmnVo5pAL81N62SPRbm7PCJgYIgXCEtFym2yyiX0tlQ90NqW7aDobPHiwOfTQQ1MOIdWTtFvq2qUyIpwQPf30ZMYStYigQhOIsBEhCTcaOriIuFRppHQKJuXXj/xjPToC33jjjTaKj2cQ4UZ6rF9TDv9h51j6fjCeGnak5bIORvTn/fffH7lVBEDulovGDA9iPWoGtmjRotxbufQhF/dMa4iACIiACIhAkglIpEvy6ZS4b6SmkM5C6gWpHTIREAEREAERKCQCiCpEOSHShWuipdsH9esQo0hRpfMrogcRU507d45sHhBeC1GEVEzWIAKKtFUELdagTl4qXxC+SMf8999/bY07/vC/3R/3MxF7vEaNNeq4xREf454bnW1JFT7iiCMCsYe0VYQjOFCrzhkpv0SwkX4K4yiDPymyCF38nYKUV/5QY61r1642dTaOEQmJmEXEGQJs/fr1bUQfNeoQN0n9jTJY4SMRgJznuuuua1OGSR9dbbXVzPTp04M9perq69blbHg+6aREy7kad5wb+2TtVH9fIg2WlF5EPObhNxGEzEEcxSfEt3Ctw/CeFi1aZIhSnD17tuXJXVpnnXWsP3AIN53w5+fKhzjnpTEiIAIiIAIiUKgEJNIV6skVud9+rRmKZ1PzRiYCIiACIiACIiACxUaAVGPEPIS/mjKEPsRHaszVlCXBh5rau54rAiIgAiIgAo6ARDrdhUQS8ItHS6RL5BHJKREQAREQAREQAREQAREQAREQAREQgRwSkEiXQ5haKncEJNLljqVWEgEREIGqECCymbQ40gLvvvvuqiyluSIgAiIgAiIgAiIgAiIgAmkISKTT9UgkAYl0iTwWOSUCIlCCBPzPY2pytW3btgQpaMsiIAIiIAIiIAIiIAIikH8CEunyz1hPqAQBiXSVgKYpIiACIpAHAvo8zgNULSkCIiACIiACIiACIiACEQQk0ulaJJKAvhQm8ljklAiIQAkS0OdxCR66tiwCIpA4AsOHDzczZswwAwcONM2aNUucf3JIBERABEQgNwQk0uWGo1bJMQF9KcwxUC0nAiIgApUkUF2fxy+88IIZO3asWbFihRk2bFglvdU0ERABEShOAhtttJHdWL9+/Uz//v2Lc5PalQiIgAiIgJFIp0uQSALV9aUwkZuXUyIgAiKQIAL5/DyeOXOmeeqpp8zTTz9tfvnll2DX8+fPTxABuSICIiACNU9AIl3Nn4E8EAEREIHqICCRrjoo6xlZE6CbYFlZmZ03cuRI06lTp6zX0AQREAEREIGqE8i1SDd37lwrzD3zzDPmiy++KOfggQceaI466iiz1VZbVd1xrSACIiACRURAIl0RHaa2IgIiIAJpCEik0/VILAFqbyDWEdLfsGHDxPopx0RABESgmAnkQqRbtGiRTWV97rnnzFtvvVUO1w477GCFue7duxczRu1NBERABKpEQCJdlfBpsgiIgAgUDAGJdAVzVHJUBERABERABKqfQGVFun///ddGzI0fP95Mnjy5nOObbrqpOeyww6w4V6tWrerflJ4oAiIgAgVGQCJdgR2Y3BUBERCBShKQSFdJcJomAiIgAiIgAqVAwBfppk2blrGr4EsvvWSef/55K8wRQeesadOmxqWzrr/++qWATnsUAREQgZwRkEiXM5RaSAREQAQSTUAiXaKPR86JgAiIgAiIQM0ToPwAZQd69+4d6cw777xjJk2aZP989tlnwZjatWubHj162Ki5Dh061PxG5IEIiIAIFCgBiXQFenByWwREQASyJCCRLktgGi4CIiACIiACImAMHVgR5YiYmzFjRjkkXbt2tVFz++yzj1CJgAiIgAjkgIBEuhxA1BIiIAIiUAAEJNIVwCHJRREQAREQARFIAoHffvvNXHjhhWbBggXm3XffNcuXLw/cos5cly5dzO67725WXnnlJLgrH0RABESgKAistdZapmfPnmbp0qVm4MCBpm/fvkWxL21CBERABESgIgGJdLoVIiACIiACIiACsQjstttuZu7cubHGapAIiIAIiEDuCPTr188sXLjQ9O/fP2Nt0Nw9VSuJgAiIgAhUNwGJdNVNXM8TAREQAREQgQIlcO6555rRo0eXi6BbaaWVTJMmTQyNIRo0aFCgO5PbIiACIpBcAkQqn3766WbttddOrpPyTAREQAREICcEJNLlBKMWyQeBm2++2f6LIWH9FCyXiYAIiIAIJIPA66+/bmvRUZOO1FdnzZo1s7Xo9t57b9OmTZtkOCsvREAEREAEREAEREAERKBACEikK5CDKjU3EefKysrstkeOHGk6depUagi0XxEQARFIPIEVK1aY8ePHBw0kqFnnjG6u1FCiRt3666+f+L3IQREQAREQAREQAREQARGoaQIS6Wr6BPT8SAL//e9/TZ8+fSTS6X6IgAiIQIEQWLx4sRk3bpyNsHv11VfLed29e3ez1157WcGufv36BbIjuSkCIiACIiACIiACIiAC1UtAIl318tbTYhKQSBcTlIaJgAiIQJ4J/PLLL2bAgAG2UDnlB+LYvHnzzDPPPGMj7GbPnh1MWX311U2PHj2sWEcTCpkIiIAIiIAIiIAIiIAIiMD/JyCRTrchkQQk0iXyWOSUCIhACRLwP4+nTZuWdVfBt99+2zz11FNWsPvmm28Cgi1atDBE2CHYbbPNNiVIVlsWAREQAREQAREQAREQgfIEJNLpRiSSgES6RB6LnBIBEShBArn8PH7xxRetYDdx4kTz119/BTQ7duxoxTr+0MVQJgIiIAIiIAIiIAIiIAKlSEAiXSmeegHsOZdfCgtgu3JRBERABBJLIB+fx8uXL7di3dixY83UqVPL7X2fffYxw4YNSywPOSYCIiACNUFg1KhRZsaMGaZfv35ZRzTXhL96pgiIgAiIQOUISKSrHDfNyjOBfHwpzLPLWl4EREAEipJAvj+Pf/zxx0Cw++CDDyzD+fPnFyVLbUoEREAEKkugXbt2hhqh1Abt27dvZZfRPBEQAREQgYQTkEiX8AMqVffy/aWwVLkmed9E1ixYsMD+63Dt2rWT7Kp8E4GSIlCdn8efffaZQbTr1KlTSTHWZkVABEQgE4GNNtrIDiGSrn///pmG630REAEREIECJSCRrkAPrtjdXrhwoSkrK7PbHDlypL6wFeGBf/XVV+bjjz+2/yq82mqrmQcffNBMnz7d7Ljjjuahhx4yK620UhHuWlsSgcIjUJ0iXeHRkcciIAIiUD0EJNJVD2c9RQREQARqmoBEupo+AT0/JYFBgwYZxLohQ4aYhg0bilSREJg7d665/vrrzYQJE1Lu6PXXXzfrr79+kew4edt48sknDedw4IEHmo033rhGHHznnXfM008/bfbcc0/TuXPnGvFBD41HQCJdPE4aJQIiIAL5JCCRLp90tbYIiIAIJIeARLrknIU8EYGiJ/DMM8+Y008/PeM+EZHo9ijLPYE//vjDtGnTxi68+uqrm9mzZ5tatWrl/kEZVkQgnDlzph31wgsvmFatWlW7D3pgPAIS6eJx0igREAERyCcBiXT5pKu1RUAERCA5BCTSJecs5IkIFDUBOjmeeeaZwR4RiKirsummm5rJkyebESNGBO89/PDDZqeddipqHjW1ud9++820bds2eDwpx6QbV7ftv//+ZtasWfaxjzzyiOnSpUt1u6DnxSTgi3TTpk1TV8GY3DRMBERABHJJQCJdLmlqLREQARFILgGJdMk9G3kmAkVDgNTGHj16BPshaopag2uttVbwGsIRAhI2evRos+222xbN/pO0kX///de0aNGixkW6ww8/3EydOlUiXZIuRwpfqBtJ+QGauqhYeQEcmFwUAREoSgIS6YryWLUpERABEahAQCKdLoUIiEDeCfipjRtuuKEZM2aMWXvttcs996ijjjJTpkwx6623nnnttdcydnj9/fffTb169fLue3U8YMWKFdWacur+os/eqE1XE910TzjhBDNx4kSL94knnjDbb799lVD/888/Bo6rrLJKldbRZBEQAREQARFIIgGJdEk8FfkkAiIgArknIJEu90y1ogiIgEfg1VdfNUcccUTwSqqmEETrIM4h1vgRdm4iEWCIOaTbvfnmm+abb76x47baaiu7/m677ZaS+z333GPGjRtnDjroIHPkkUeaZcuWmQ8++MDMmDHD1mSjecKuu+5q2rdvH7kG46jlRgpupq6z+IhY1KdPn5T+0NmW9F6eTV02Igh32WUXc/zxx6dN+4TP0KFDDX9RHzx4cCDs4dtbb71lvvzyS/PDDz+Yv/76y9b+C6exfv/998GznHPvvfeeqVOnjhW3qkOs45x//PFHM3DgwCCSjs6+2223nfUjGx/mzZtnHn/8cbt3V99uiy22sN2gSa1Wwxl9FImACIiACBQLAYl0xXKS2ocIiIAIpCcgkU43RAREIG8EEKsOOOCAoPYYwslZZ52V9fOWLFli59FgIJUdffTR5qKLLrJCj29ffPGF2XnnnYOXEOsOPvjgILXWHzts2DCzzz77lJvP+NNOO82+du6555pTTz01pQ+PPvqoueCCC+z7999/fwXhEB6jRo0y55xzTso1EPeuvvrqSLEK8QlxEnv++edN48aNbadc0oPDdsUVV1hB0tlDDz1kLrnkkozsqRVYt25dm9643377ZRyfzQAEwbhr4schhxyS0mei8IjGS2VEZN5xxx1m6623zsZFjRUBERABERCBRBK46aabDDVChwwZotqgiTwhOSUCIiACuSEgkS43HLWKCIhABAFEtb59+wbvUJtuzTXXzIrV8uXLrXD20UcfBfP23Xdf07RpUxt59+mnnwavIywh1vnmF73P9GCEIaKy/Ai0a665xoo9GJF7b7zxRspoL6LxiO7CbrnllnJ1+HjtgQceMJdeemngxmabbWa7mrrIQPcGkYFXXnllOXcR+Jo3bx68dvLJJwd+Re2rV69ehr/QO7vsssuscBjXEFdvvfXWuMNjjUNYPPHEE2ONZRDn8eGHH1YYHxboYIgQi4D53HPPBeM5LyIva6IxRuxNaqAIiIAIiIAIiIAIiIAIiIAI/B8BiXS6CoklcN9995mFCxfaDqBKW0vsMaV1DIHORb8RgUYkWrb2zDPP2NRNZ379MuqQIXq5zrCIOghe/NdZWCh0r++5556ma9eu9kffr9tuu83QeTTV/FSdZ8PNMUjz9Wu/fffddzal0xkRd0SCkT5LKu+FF15oHnvsseB9BC1EPGfhrqw+R1J9+YMgNWHCBPsWohXRc84QD+G0aNEiM3bs2OB1UoARQt0ffEHUokZgqvTfbM/Qjf/111/NXXfdZX7++edyvnEWnBnniR/4AJfu3buXOwvWYcwee+wRiKG77767XdOlydIxlgg814Tk4osvtmnEMhEQAREQAREQAREQAREQARFIOgGJdEk/oRL1D3GurKzM7p4uoKT5yQqLAGLKJptsEjiN2Eb9uGwMsQaxiVpr2HHHHVch/fHPP/80HTp0CESZq666ytA51BmCFEKvb9So69atW/ASQh9RbtgZZ5xhzj777OA99oG49tNPP9nXwhFqbiCppE4UYzxprb4hypEOiyFK3X333eXeD6fl3nnnnWavvfYKxnz77bcVmisgbJH24sZNmjQpEKSocUett7B99tlngThJEw/XYTWbc8nFWL+bLzX/1l133VjLhkVbIh+bNGlSbq4fsQgj6g9mqiUY6+EaJAIiIAIiIAIiIAIiIAIiIAJ5JCCRLo9wtXTlCfgpihLpKs+xJmcijPj13fi5QYMGWbkUFqaeffZZ065duwprXH755Wb48OH29WOOOcaQ2uksXIstqu4c3WZdrbyoNE+aNVx33XXBmqRg+tF6NG7o2LFjIBSGo/GYuOOOOwZiox8lR4Qdgh615Xx7++23yzXQmDNnjo0g8y0cbeeL2wiPxx57bAVWiFoIjRiReqxR3Ua0HM06nFGrrlGjRrHcIDKOaEaMKDp37v5kBFWEW2dRQl6sh2mQCIiACIiACIiACIiACIiACFQjAYl01Qhbj4pPQCJdfFZJHenXH6M2GKJTtkbqKumYzubOnRtZD47IOFfDLSzcIMpde+21aUUdvwNtVBQcHVO32WabwI+bb77Z9OzZM/j56aefthF4WFTdOkS8Nm3aBON5HnccRi+99FIFLKR6u1Rc92Y4nZZIPCLywkbtPhpt0CW3Vq1aFd7neQiZGHtCoKxuo8OrL7YiQK666qqx3CCVdfr06Xbs+eefb6jNF7Zw/b5U4m6sB2qQ4bwQwps1a1YhKlV4REAEREAEREAEREAEREAEckdAIl3uWGqlHBKQSJdDmDW0FPXVEFGwVKmXmVx78sknTf/+/e2wdKmZfkrrFltsUa55wA033GCIbMMGDBhQrr6de74f9ZfqOaTMulpuvpBHSi6ps66BRVQE2+zZs83ee++dabs28hBm+BA2hCkEKoxGCek63aZ7kC+eVvZcMm4kw4Aff/zRRh46mz9/fuwliZBzqce33357ym6xfifcqE67sR+ogVZQpuswRt1DxDqZCIiACIiACIiACIiACIhA7glIpMs9U62YAwIS6XIAsYaX8CPYELGIdsvWqOFGLTeM9MiXX345cgk6qd544432PereUbfMmZ8KS3OGqO6iX3/9tencuXMwh/pw4Sg0P02UgePHjzebb765efHFF4O00qjGFYylC+1hhx2WcvtEttHR1a/hFx7sN8CgSUQ2nVr9tfyaboiCnFN1m887VQfXVD75texoGEFzibCFIxdTNfuo7n0X6vP0eVyoJye/RUAEREAEREAEREAECo2ARLpCO7ES8VdfCgv/oEnZHDRokN3IeuutZ6NxsrWwuBWuBefW6927t3njjTfsj/xvouec+TXMzjvvPHPKKadUcOP3338v10k1VY00/zlEFlGnjk6wdBTFzjnnHHPaaadVWN9v1uDeJC2X2nAIbnRTzWSIgi61c4cddijXCTbTXP99PzU3qv5eNmtVdmxVRLoePXoYUn+xcJMP54//+cFrr7zyimnevHll3S35efo8LvkrIAAiIAIJIED9WhotEdmviOYEHIhcEAEREIE8EZBIlyewWrZqBPSlsGr8kjA7LLA9/vjj5aLVwj7SRZVosXXWWcdsvfXW9u0FCxaYLl26BENJf/XTJHkjHDUVTjeliYSLOkPkcim44edvtNFGwUvhhgzuDb92Ha/deuutQS06fk4l7v3222+GCDBnEydOLFejzvfl448/NtTeo9FEw4YNg7f8zq3hlN5sznvChAnmpJNOslNqqnFEuMZfNo0dzj33XNvxGaPzr+uo6zPwIyt5/fPPP1d312wuSWisPo+rAE9TRUAERCBHBKjlSo3QgQMHmr59++ZoVS0jAiIgAiKQNAIS6ZJ2IvLHEtCXwsK/COEOmwhLTzzxRLmuqG6XU6ZMsVF38+bNsy+5TrA0ANhrr70MzRCwKJHNTzdlzOjRo822224bACQNFtEGO/TQQ83gwYMj4frdV1M1ZcCffffd1/oXNiLoiKRLZf76qSL6EO9OOOEEuwQReq6WXvh3Il19vkw3B5Z+iiiRde3bt880Lafvw5FUYcRLjGjH448/PtYzJk+ebI477jg7llRZUqARdp0h9hKh6KIbqxJ1GMuhEhikz+MSOGRtUQREIPEE3D8mEknn6vUm3mk5KAIiIAIikDUBiXRZI9OE6iCwcOFCU1ZWZh9F1AxF4GWFRwBB7M477wwcJ0KOSChqr5ECSkMFRBbXrZOBpMZOnTrVrLLKKnae3+iAn08//XTbYAGhiu6vpK86sSeqM+sDDzxgiK7D6IaKABdlhx9+uH0uRh27o446KnIcgmLUe/iy9tprpzwkBEon4iEuUQsO4W7llVe2LIj2GzFiRDAfMXDo0KHBzzSmIEXWWTbNFnynli1bZlq2bBm8RK0/Iutgir3//vs2PRS/0omOVb2NRx55pH0OBg98oJPvmmuuaSPf4Mx/L7roItOoUaPgceFGHfjP+VKLkAgDmknA2hkNTBDqZJUnIJGu8uw0UwREQARyRUAiXa5Iah0REAERSDYBiXTJPp+S9o7IKsS6IUOGlEv7K2koBbZ5RBM6iLpunJncR6yhyL+f0rp8+XJDYwUn6KRbIyoq7Lnnngvq0G2zzTZmzJgxkUsgSDlx56yzzjJnnnlmykcdeOCBZubMmcH7iHYIe+kMcYz6c19++WW5YezZiYzujbXWWsv64otpS5YsMVtuuWUw95NPPjF169bNhDTyfV+4TLcAKbatW7eu1DMyTSLSjWjBTHbVVVcZBFTf/E636eYjag4fPjzTI/R+BgIS6XRFREAERKDmCUikq/kzkAciIAIiUB0EJNJVB2U9QwRKmMCPP/5oTj311IyNIxBULrnkksgC/whc1JIjlTXKiKq76aabDCJc2Eih3XXXXe3L6VIf/cYM1157rTn44INTnlq4MQG16vyadqkmIlYS+ZeuiQYRYffee29kVB4Rpd98841dPlUTjThXjXTTa665plyUY3ge6cmInrVr146zZKXG0GmWcw2LlG4xBExE1hYtWlRYnzp2dMRNNZeU2AEDBsRqylEp50tokkS6EjpsbVUERCCxBCTSJfZo5JgIiIAI5JSARLqc4tRiIiACUQRcUwiiz+jCunTpUtOkSRPTtGlTm6ZItF2miC2EJVIxEQyIwiIdlrRZ0h0R4erVq5cS/qOPPmpIDyWdslWrVpHj8PHBBx+0vh177LEZozeJRiM9luYFpG7GNZ5DHT32QG070jcbN25s66rRJIM0b5fqG16TvT/11FO2sQbdZatqc+bMMTSSwA+iHuvXr2/FRmrUUbeuTp06VX1ExvmLFi0yNAQh9ZnIWc4RFtwLfCCqMJUtXrzY3gci6xBASZVG0IMPNe9kuSHgi3TTpk1TV8HcYNUqIiACIpAVAYl0WeHSYBEQAREoWAIS6Qr26OS4CIiACIiACOSfAAIu5QeaNWumYuX5x60niIAIiEAkAYl0uhgiIAIiUBoEJNKVxjlrlyIgAiIgAiIgAiIgAiIgAgVKQCJdgR6c3BYBERCBLAlIpMsSmIaLgAiIgAiIgAiIgAiIgAiIQHUSkEhXnbT1LBEQARGoOQIS6WqOvZ4sAiIgAiIgAiIgAiIgAiIgAhkJ0K2cGqGXXnqpaoNmpKUBIiACIlC4BCTSFe7ZyXMREAEREAEREAEREAEREAEREAEREAEREIEiISCRrkgOshi3cd9999luj/369cvYabMY9689iYAIiIAIiIAIiIAIiIAIiIAIiIAIlA4BiXSlc9YFtVPEubKyMuvzyJEjTadOnQrKfzkrAiIgAiIgAiIgAiIgAiIgAiIgAiIgAtkQkEiXDS2NrTYC1Nzo06ePRLpqI64HiYAIiEA0gQ8//NBMmjTJdOvWzbRt21aYREAEREAEREAEREAEREAE8kRAIl2ewGrZqhGQSFc1fpotAiIgAlUl8Msvv5jLL7/cjBo1KliKqOYhQ4aoaHlV4Wq+CIiACIiACIiACIiACEQQkEina5FIAhLpEnksckoERKBECBA9d/zxx9u6oHVXb2A6duttZk+faH7+7itbI/See+5RGYISuQvapgiIgAiIgAiIgAiIQPURkEhXfaz1pCwISKTLApaGioAIiEAOCUycONEMGDDAEEnXdodupveAIaZu/Ybmz19/MePuGGTenjzaPu2GG24wvXv3zuGTtZQIiIAIiIAIiIAIiIAIlDYBiXSlff6J3b1EusQejRwTAREoYgKktiLQYR32OMj0PmdIhd1Oe3K4efbOyyXUFfE90NZEQASSR4DP5xkzZph+/fqp5EDyjkceiYAIiEDOCEikyxlKLZRLAhLpcklTa4mACIhAZgJxBDq3yluTRpnRN/yvmKeIusxsNUIEREAEqkqgXbt2NsJ54MCBpm/fvlVdTvNFQAREQAQSSkAiXUIPptTdkkhX6jdA+xcBEahOAr5At+9JA01Zr8xfACXUVecJ6VkiIAKlTmCjjTayCIik69+/f6nj0P5FQAREoGgJSKQr2qMt7I1RrLysrMxuYuTIkSpQXtjHKe9FQAQSTMAX6A4acINtEhHXfKFuwoQJpm3btnGnapwIiIAIiEAWBCTSZQFLQ0VABESggAlIpCvgwyt21wcNGmQ7Cw4ZMsR2E5SJQFUJ/P7772bx4sXmf/7nf8ot9dhjj5krrrjCCsN0rZSJwNixY80777xjli9fbv7++2/D3fnzzz9N3bp1zcUXX2zWW2+9ooBUFYHOARh1/dm2mQSf0/yjioS6orga2oQIiEDCCEikS9iByB0REAERyBMBiXR5AqtlRSDfBP755x8zd+5cs8kmm5jatWvn+3EFuf5HH31k5s2bZ0WW1VZbzVx44YXmp59+soXxTz/99GBPHTp0sK9jL77umfs9AAAgAElEQVT4omnZsmUi9otI/cEHH5jtt9/eNG7cOBE+lYIT33zzTdro3bPPPtucccYZBY8iFwJdlFA3bdo0/cNKwd8ObUAERCBpBCTSJe1E5I8IiIAI5IeARLr8cNWqIpB3Avvvv7+ZNWuW2W677QxftmX/n8CUKVPM9ddfbwWuKCMKirqHztxffPn52WefNRRnrml74oknzDnnnBO4MXz4cLP77rvXtFuxno8oescdd5h69eqZQw45xNSvXz/WvKQMImJuhx12CITbsF9EXR555JFJcbdSfuRSoMOBP3/9xdw94D/mm3kf2Ug6IuoUAV2po9EkERABEYgkIJFOF0MEREAESoOARLrSOGftssgIfPfdd1acc/bxxx/bSLFSN6ILEefuvPPOjCiIQnQRiL5IN27cOLPllltmnJ/PAcuWLTNbbbWV+e2334LH7LjjjmbEiBH5fGzO1p4+fboV57CDDjrIpqwXmnEGX375palVq5ZZaaWVzKWXXmoQf7Gbb77Z9OzZs9C2FPiba4HOLewLdZ06dbJCnUwEREAERCA3BCTS5YajVhEBERCBpBOQSJf0E5J/IhBBICzSzZkzx6y66qolz+qiiy4qJ2S1atXKnHzyyTaS67777isXPUcqLJFeK1asMM2bNw/YPf3006Z9+/Y1ypI6aNTHI+3S2b777muGDh1ao37FfThi1lFHHWWHb7PNNmbMmDFxpyZ2HN30qFOHESW49957J9bXdI7lS6Bzz1z83UJz60ndzZ+/LTW9e/c2N9xwQ0FyktMiIAIikDQCEumSdiLyRwREQATyQ0AiXX64alURyCuBH374wYofzvyosLw+OMGL33vvvbb5g7MDDjjA3HjjjUG0HIx222234P1PP/3U1KlTx/z777+mRYsWwetPPfWU2XrrrWt8pw8//LBtUICtvvrq5tFHH61x8TAulLfeesv06tXLDi8Wke7UU0+1qdAYgm/Xrl3j4kjMuHwLdG6j38z90Ka+ItQde+yxNgpRJgIiIAIiUDUCEumqxk+zRUAERKBQCEikK5STkp8i4BFYtGhROSFp/vz5Jc2Hjq1+9Nuee+5phg0bVq6hxq+//mpThEkhJVWRlEWMqLWNN9444Pfkk0+ajh07JoLnV199ZRATEQ0bNWqUCJ/iOEGUYvfu3e3QXKU9UicOUZXU08oYEZOsUdm08BNOOMFMnDjRPvqRRx4xXbp0qYwbNTanugQ6t8F5s/5r7jmnj/2RaDqi6mQiIAIiIAKVJ0BtWurp8g8fzZo1q/xCmikCIiACIpBoAhLpEn08ck4EogksWbIkqJtGlNWHH35YZVSk0FLzjPp2/KEeF1FQ2267renRo4dp06ZNhWf8P/bOA1yKImvDhQmzq6KAooi6KOgVw6og5oxiQBFMGEDMgWTcleCaFTFhAFTMIpgxgJjFLBhWzGEFJRhAMSGG/3nLv3rr9u2e6ZnbM3fCd56HB+5Md3XVWz1zmW++c85nn31mzjvvPOtGw8W22mqrGcZ57bXX7H8kFyxYYMUzRLGk4gjnT5kyxXz66aeG8akNRlrqBhtsYFMM//a3v9WZB3Xorr76avs4tdzGjRtnBZ1w0C31rbfeMrvuumsg4IVFOsQMxLz58+ebiRMnWg5z5syxXXQ5b80118zK+u2337Ypnh999JHdG8QhOrQi/h1yyCEZO7X+9NNP9tqwY26IS02bNrVuumwxcuRIQ0096sDR2AB2NM94+eWXzTvvvGPFyB122KGgjjx4cf/07t3bTheWo0ePNosuumjOItvzzz9vHn30UTt/xEo3HgLgEUccYcfMFHDk2txPjIFAy/4hep5yyil2T5PGkUceaZ588kl7OE092M9cgnv58ccft/cDIjvCMvcVTTbYs9VXXz2X4XI6ttgCnZvc6xPHmnGXDrA/jhgxwiCeK0RABERABERABERABERABOIJSKTT3VGyBEgpQ1ShFpS6BNbeJl+kW3nlla0IkW/QbAFn0MCBAzMOcf311wfuKHdg//79rSBGkJpJSumdd95ZZxzEvptvvjljl08EFa5x1VVXxc4jKnXy66+/ruV8y8fl5DeOoNg9teC478KBUPbwww/XSo/1j2FfaJLAWuMCkYhvw1u3bl3rEPaBFN24jrQIRJlEJUSg7bbbLhgT4efAAw+s1XzCPYnLcM8998z3lok979hjj7WiWraAI/ctr3HqBoYDcfLKK68M3I5R4+HQ4xgEzKhA1MP99sknn8ROB3G3W7du2aZrn0f0fOaZZ+y/c3FbIsxddNFFgcgYdbGzzjrLHHPMMYnmketBDSXQuXlOunWYeeLWy+17OK8tOr8qREAEREAEREAEREAEREAEoglIpNOdUZIEEOconE/wwY4P5Ir/Efj+++9NTU2NfQDR57nnnssbz7nnnmtwYCWJsDjRvXv3Ws0YMo2BiOfcVeHjvvnmG7PLLrsY/s4UiDtvvPFGLZecP38cUtSUyzV8kY60PISNuEBIQxwKB8LS3nvvHSuyhY8Pd+SdNWtWRncWTkWEorjAuch+JAk4UjcuqbsxyZgcg0svkygWHufCCy8MusD6z7FWagy6oLMtTk7cgHSOdYGzMere/fLLL02HDh2C4xAEO3XqZJ2FkyZNqnWfPfLII9almS3oVuuunbS5CGLsOeecEzk0e+C698atI9ucsj3f0AKdm9/YS/qbKY+Pk1CXbcP0vAiIgAiIgAiIgAiIQNUTkEhX9bdAaQLwBQeJdHX3aN68eTatk8CJhPCQTyAU+SloiBk0W0AgJYUVVxRpgS7uuuuuWuIHaYfUH/ODMejsybzohknKKBEnJpLOiePJHcexJ554ok1tpeYKwh1NE5wY4xftx33mu8twsG2//fY5o/BFOv9kRL+dd97Zzu3NN98MniKNdfHFF691HeZ45plnBo/h+kNARFxCVKUjKH9cuMYV/iDwRYii7hrjv/jii4HoR1rxoYceGrs27oFevXrVeZ79dU0OTjvttOB5HIuIimnGq6++ap2G77//fiBose+wQMR06bvcW6uuuqrdZ/72wxfoeRymOPRc+MITj0UJZn6X3+bNm9tjnOMO5+VRRx1lpk6daoekmchNN92UFcP+++9v07gJ1rjhhhtmPIf7xecLh5NPPtkKsfz7iSeesE0VCNKQn3rqqaxzyOWAUhHo3JxvHdzbTHthohXqeF9RPaVcdlPHioAIiIAIiIAIiIAIVAsBiXTVstNltk6JdJk3DOFq0003tQch1j344IM57zDiGKl+r7zyij0XcY2UynDNN1yMpH8SCAl+kwX/OSd40JDBNTkId6ENu8c4ByHPTy1lLU6AdItiXtQEI6644gpbI4+g9lvnzp2DtePiylanLAoUKXjO1cTzuJyoKdemTRt7OHXWcHO54P5E/HHBfvC8GwPhByeYPxdffEpaRxCnmRP2hg0bFnRMjVpDmCPHIGzi0nJBsWlqtBEIRqQrFyJIeT7jjDPs0D169LBiZdLwBTb4P/bYY3VOxZHpRF32f/jw4cExYZEvzIADEUIRgV0w1nrrrZdxir5Il8R9hwhKwwQCUY572Bd2qTmI2497J9/XcNyEqXuHc5Do2KWn6Xxcw3dX/eWH723H15mfvGtTXvnyRWUMkr4qdJwIiIAIiIAIiIAIiEC1EJBIVy07XWbrlEiXecPo5rrtttvag/Ltnul34GScuDplvsuMD/9+AwP/OZxF1KcLp1AiJro01qi6aieddFIgMlIXL8oNRl0v3E+EL1bhqhsyZIh9nOvjcMon/Dly/q233hrwdeP5qZwIR07A4/lbbrnFnH322cGlaXiwxhpr1JoKteZcHbikoszgwYMDl9d1110XCC9RawzPIWo/ER779etnT49L282HX/gcrk0dNoJaa9RcSxqInYiiRNz9QJdV3JdE2IVGLT4cekRUerSbBw5J14wiqt5ieL4Iw859l0SkQ0zGlermQbo3Lk+aq7jg+txLe+21l1lrrbWSIsp4HCIlAh3uzU136WoOOHVoKuOmMYgv1OX7vpXGPDSGCIiACIiACIiACIiACJQqAYl0pbozVT4viXSZbwDfCYTYQO2rXINOrriWnIgQ1SH2559/rtXVFXHQBSmLrVq1Cn4eP358UCfPnwspfy5VNJwuy3G+KEMHzmbNmtVZii/K4E6ibhzhi1g85pxLubLwHYFx4oHfOCDs9jvhhBMM6yfCzi43F4Q7OrsSSVMsSfUkjZbIlsrrC2Nx98Szzz5rnW0EXVcz1d7LlaF/vO8A7Nu3b2QTjqjxw+nLcQ0awqmkNM1o1KiRHZIuvzSEIGikgXgZFX631jgxMO4+TiLS+aKsPw6OVfaftFeE3yZNmtQHdZ1zEeh4LZeaQOcm6gt1OGi5PxQiIAIiIAIiIAIiIAIiIAJ/EZBIpzuhJAlIpMu8LT6frl272o6iuYaf+hgnTPldZMMpmj/99FMtNxmdXRdbbLE60/BTE8N10JI2wEAUOe644+zYfkdOUjapN0bUp0Om76TDAUZX1HD4jj8cg5tvvnlwiO+yI4WUeYXDT9nFUYeoli0GDBgQCGnZutYiULrOuJzHfMPhC0f1bTiSae6+eIoQ7Fxv2dYbTiuOE23DKa1vvfVWkGJ96qmnmrvvvtteKlOqLfX5SLkkqHnn1xOMmid75jrvJhHpGAMR9IILLsjYEAVHI3MOOy+zsYp63jWqaL52G3P0pXebJZddPp9hCn7OzI+n2dTXX36cbyZPnqz6dAUnrguIgAhUAgG+sCQLgnqmKhdQCTuqNYiACIhANAGJdLozSpKARLrM20Ja5/HHH28PIj0UJ1CugYuFOmYEXUEvvvjiOkNQZH+zzTazj4dFOr8uHs/7Ljt/IN8NFu7w6jsCaS5AOmZU+CmMvohGIwXX2RbR0RXiz5WFX5Muzr3li3Rhwcw/n5p8Xbp0qTMF0hpJ/SRwFzpBLdNc/T2iuQEOrLigi6hzVMYJluGup74DLVdmmY7368pl60rrj0P6Jy5AF3SgjXKahTvZ+mnY/j7hlkMwjAqcl64eI+mxCGWZwneEcj9utNFGiZDhDkRsRIx65plnIrv/4q5DMKTZSn3Cueh6XzLGrN2utDtij792iJl83432NctrVyECIiACIpCZQE1NjS1lkMT9LZYiIAIiIALlS0AiXfnuXUXPXCJd5u0l9dEJc7mkE/qj+ul+RxxxRFDbzT+GtE7fkeW75WbNmmVT9lx8+umntitpOHyHV7g+me+IytSl1q+3hjPp4IMPtpfxXXoHHXSQIc0yn/Br64XrzbnxEEVdzTvEMF9M8s+Pqx3nC1ek+JJunC3YW0RDIltNOgRQaukRp59+eiDi+tcIux99B1q2ueTyvC/MxjkTo8YLzy/OPejXe0PgmjJlSjAcrtIrr7zS/kx33vvvv7/OpcJp3H4Kddw6/Zp0jMnY+QTuVLrEsq8uRZpxuKe5t+sTrtuyRLr6UNS5IiACIlCaBNz/NVQqoDT3R7MSAREQgbQISKRLi6TGSZWAL97gMCEdU/E/AggfLl0y7E5LyslP94sSM3755RdbgJ6OqS4QQxBFCN9lx8+kAi633HJ1Lu83dwineXINv6tmuDGFGwwB7oUXXrA/4vjD+UdQmB/BxkU20QmBZNKkSVZcbNGihT0tXAeN56McTaRskmpCUPeMYv8u/Jp2iJqkm/qBgEnTABeZBEn/PD/dNc6h5473U0xJDXbdVcMbkkSQTHoPxR3np1LT8MNvqpFtbJ8la3Bpzv55vguO7rV0cHUR7nIblYYdduIhvtJ4JFP43V3j3Jb++S+++KLhfYz7ZMkll4wcmtRoUqeJNBopBOmu67Q1R18yprTTXU/tbqhPp3TXbK8IPS8CIiACfxGQSKc7QQREQASqg4BEuurY57JcJV07+ZCLM0a1N2pvoV+LzXeWRW00IhS1vhAK/M6S4W6gvjj1559/WqdeuOi+3xwi7EZClPDHd3PxU3OjxCk/VTQsfjEGgohfXB5hDsGEYM5+N1hqkJFe6ZoIuDnAAFcW4uaPP/5YSxD54YcfzAYbbBCge+qpp2zH0HD4zsOw84qaZo8++qg9pXnz5ubpp58OhBmu161btzppjoifiy66aMbXpu++wyWIWBkXvmCZyZXlN+oYMWKE2W233VJ/f/DvLdKkSVsNd/2Nu+i5554biG6kQCPS+7UOw2nWpKm6bq6MOWfOnFr1AqMabpx//vmGjq4u3n///VghzR2DMIy4R1DzzneRhtfy6quvGmpFEoiziGfheo3UFeI+5v4g8hXbw9d2brrNdj3AdB1waep7W98BbeOIU7sb6tLJDVJfmjpfBESgmghIpKum3dZaRUAEqpmARLpq3n2tvWwJ+E4iuomSerlgwQKDU2zevHm2UD3pqNOnT6/lhPMFqLATDgGNOmkIR4hlriGDDyksTvmurLhi+qT2OVGNscK16/xaagg6pHXSlIHjEOh8MYXzcc6RekjQYZZ/u+6xPAYbBLUVVljBFljG4Ufaru8I9JtthEUdurBGFfH3u7uG66z5XVOZA80AcCpSAw6xk3mEg/pka621VvAw+0WNuF9//TV4jLXCj6D+ni+orb766madddYJjh09enRQ24vjEOCiwq/jB/vDDz889dcBotx+++0XjEuXVVKqEQipp4OIBWdEOLeX7uBwGjVrwcXYpk0byweuroED9wtOrBVXXLHWGnxXIU9w33bo0MEKhQjNfg3HcLo47s7hw4cbHHi8pkjhXnzxxYNUZ8bDEQp7HufP0ksvbRDHmjZtaucxceJEm4rtAichjkICVyXC47XXXltrztTHc+fXZ0P4YoO5zJ8/35SaUOcLdGk4B+vDSeeKgAiIQLkRkEhXbjum+YqACIhAfgQk0uXHTWeJQIMS8LuJ5jIRUmQRGFyQJohzKS5whZHe6kSRcOqi78qKqx8W7thJc4AlllgiuOQHH3xgdtlll8TLQLRDhHAxderUOkJPpsEQI++8806zyiqr2MMQ7+Dpj7fSSivVGcJPuY1qzOA77aKuj6MKh53PnlRNYu7cuWbjjTdOzMAd6KcH+47FTE04/O6n/fr1M6ecckrO1812Ak5M6g+69OC448PNSNxxiGRRjUzC4/jil//c7NmzrVA6c+bMjFPl3qbxCPNwQVp1Jsdi3IC+ezHs9uMcruFcc+Exohyk2Rhnep77glR1omOXnqbzcQ3fmMEX6BBccSPKIV2fXda5IiAC1UZAIl217bjWKwIiUK0EJNJV685r3WVNwHd1ZVsI4kCrVq1soXtcSP4HY8QUBJFLLrmkzjCcR4F80jhJpSToLkqXURd+Y4OxY8eaLbbYos44XIPzEMMQRXCGhRtM0NUVwSgqmAfpqK4TZ5QYSC063FbZRBncTYhSfu08BB03b67FWOHUROaFe27UqFF2ijRo2HbbbWtNFwEGHlHCFKIEa8RN5tbhpzf6c8i2n/7zOPRwcRG+2LjVVltZITIqcDy6Om+5NHXIZV4ci6uTtGxfmAyPkaleHYxhFBeIeKQRh1Ob3fE4JBFOncAcHgd3HynE4RRt3I84U+MEtbj5hB15d9xxh6GBRqZYc8017X3l1yvMlXPc8bweXW3EnXv0NTv16JPW0DmPg0B365De5pM3X7KvPZqzuJqQOQ+mE0RABESgSglIpKvSjdeyRUAEqo6ARLqq23ItuBII4NQhxZJaa6TbNW7c2P6h7hyiDR+El112Wfu3E3EyrZv0xMcff9y6ihgDVxeCVrNmzWzqLI45RItw/S/SDxFTEAEPOeSQWMHknXfesamrONa23nrryKngiGMO/I2zDGGOPwgm1DhzzQFIw41ynXEO5yMCum6fuOUQYTp27GgQZVzTi/AEcKHhPtp7771rNbLwjyONmPpmuOxwWkUJeb///rtNdWRvSOmEH+wQVUm19F1aYbGR+nrwZFxETP64f/M3acj+3zU1NXXSIxGGSBMmnTeq+QXr4Z5hHaRD9uzZs+BuJliQkoqguHDhQntP0iyEdEf2JVOwFurAwZLOr9xn1AskdTWq/mF4LFJXuR+ol4iDk/0nTbV169Z2X+IEPq711VdfGQRm94fUavaXvwn3b35u0qRJpOjEff/EE09YYZbXFtdnDfwhTZ05ZKtLWJ/3K1+oa6jUV99Bx97joKMOpUIEREAERCA3AhLpcuOlo0VABESgXAlIpCvXndO8RaCIBBB2qCUWlQZajGn46b0Iiogi5Ro03EDgQURViEChCeDspIssouza7dqbHoNGFq3rqwS6Qu+uxhcBEagmAhLpqmm3tVYREIFqJiCRrpp3X2sXgTIg4Neca9eunW0CoRABEUhOAJcoqcEIdc3XaWuOvmRMwYU6CXTJ90dHioAIiEASAsOGDbPu8qFDh6pkQBJgOkYEREAEypSARLoy3ThNWwSqgUC4AQA1tk466aRqWLrWKAKpEqDrKzUASTtectnlrVCHYFeIkEBXCKoaUwREQAREQAREQAREoBoISKSrhl0u0zWOGzfOplhSN0tRuQTo7vrtt9/a5g1+Q4knn3zSDBo0yNAdlqCpAwXnKbavEAERyJ0A76c46gop1Emgy31fdIYIiIAIiIAIiIAIiIAIOAIS6XQvlCQBXB+uqPyYMWNskXlF5RGgPttmm21mm1IgvtEFdsGCBeaNN96wQoIfdJXleYUIiED+BBDqhgwZYvgShOg64FJDU4k0QgJdGhQ1hgiIgAiIgAiIgAiIQDUTkEhXzbtfwmun5kb37t3tDCXSlfBG1XNqdNFs06ZNxlFw0A0ePNg6gBQiIALpEKCZhBPqOh83yHTsUj/HsgS6dPZFo4iACIiACIiACIiACFQ3AYl01b3/Jbt6iXQluzWpTwzH3DXXXFOnIUTz5s1N586dzfHHH99gXWVTX6wGFIESIjB27FhDnUcCNx2uunxCAl0+1HSOCIiACIiACIiACIiACNQlIJFOd0VJEpBIV5LbUtBJ/fHHH2bWrFm2AyWpr0sttVRBr6fBRUAEjEGoI/2V113brXYzBwy4NKfOrxLodBeJgAiIgAiIgAiIgAiIQHoEJNKlx1IjpUhAIl2KMDWUCIiACGQgMG3aNJtOjlBHx1c6v9IBNltIoMtGSM+LgAiIgAiIgAiIgAiIQG4EJNLlxktHF4mARLoigdZlREAERMAYg1B31FFHmS+++CKRUCeBTreNCIiACBSXwIQJE2xTrZ49e5rll8/+RUpxZ6eriYAIiIAIpEVAIl1aJDVOqgQk0qWKU4OJgAiIQFYCdH7FUceHQBx1PQaPNCs2bVHnPAl0WVHqABEQARFInUBNTY3hfXrgwIGmV69eqY+vAUVABERABEqDgES60tgHzSJEQCKdbgkREAERKD4BX6gj5ZXUVwQ7F3NnzzC3Du5tZn48zXZmvvvuu+XoKP426YoiIAJVSKBly5Z21X369DF9+/atQgJasgiIgAhUBwGJdNWxz2W3SlKvOnXqZOc9ZswY0759+7JbgyYsAiIgAuVIAKGuf//+ZuLEibY23c49+pqOXXqaKY+PMw9dO8TgpJNAV447qzmLgAiUMwGJdOW8e5q7CIiACCQnIJEuOSsdWWQCvXv3NtOnTzejRo0yLVrUTbkq8nR0OREQARGoKgJ0fb3xxhvrrLlr165m6NChVcVCixUBERCBhiYgka6hd0DXFwEREIHiEJBIVxzOuooIiIAIiIAIlB0BSg8g1uFuJgYNGmSLlitEQAREQASKS0AiXXF562oiIAIi0FAEJNI1FHldVwSqiMDrr79ucEY2b97cPPDAA2axxRZLbfUvv/yyOfLII02rVq1sfaxlllkmtbFLcaBCsizF9WpODU/ArxE6efJkOZsbfks0AxEQgSokIJGuCjddSxYBEahKAhLpqnLbtWgRKC6B448/3jz88MP2og899JDZaKONUpsAXc5uvvlmO96IESPMbrvtlsrYb775ppk7d67p0KGDady4cSpjpjFIIVmmMb9SGOPHH380s2fPNmuvvXbe0/nkk0/MqquuapZddtm8x/j111/tPBCno4Tpb775xvz888+madOmZvHFF8/7OoU+0dWoo+wATjqFCIiACIhA8QlIpCs+c11RBERABBqCgES6hqCua4pAlRHYe++9DaIXcf/995tNNtkkNQIDBgwwY8eOteNdccUVZt9996332P6YOPOeeOIJK7SUQhSSpVvf1KlTreMRwRORspwC4WvTTTe1U+7Xr5855ZRTcp7+JZdcYq6++mp73jvvvJOXUPfkk09ahyeBWDh+/PhaLk8689177732ee4x3GrLL798znPVCSIgAiIgAtVBQCJddeyzVikCIiACEul0D4iACBScwM4772w+/PBDe53HHnvMdoZMK3yx46qrrjKIWPWJt956y+y11161hjj99NMNDrZSiEKydOvbf//9zWuvvWZ/nDRpkvn73/9eCktPNAccm26v/vGPf5h77rkn0Xn+Qdtss435/PPP7UN33HGH6dixY85j7LDDDgY3novrr7/e7L777vbH+fPnmw033LDWmOpinTNinSACIiACVUVAIl1VbbcWKwIiUMUEJNJV8eZr6SJQLAK+6PHMM8+YtdZaK7VLn3TSSebBBx+0411zzTVmzz33rNfYn332mdluu+1qjXHeeeeZQw89tF7jpnVyIVm6Ofpuvdtvv91svfXWaU2/4OOkLdLdeeedZquttspp3lEiHPcpDk3ixRdfNAceeGCtMa+88kqzzz775HQdHSwCIiACIlA9BGjiM2HCBDNq1CjTtm3b6lm4VioCIiACVUZAIl2VbbiWKwINQaB9+/Zm5syZ9tI0emjWrFlq0/BrtF177bVmjz32qPfYvvCHi4y0xFJJRSwkSwcOQfK5556zP5abSPfoo4+aY4891s4dcQ2RLdfwXXCkUm+xxRY5DfHuu+8Grjl34q677p39onAAACAASURBVGpGjhxpf+Tvc889t9aYfPg64ogjcrqODhYBERABERABERABERABEagsAhLpKms/K2o1fFv4xRdfmJ49e1bUuqpxMdQIo1YY8cYbb5gVV1wxNQxHH320/WaZCIt0f/75p2nUqFFe1/rPf/5j0xI333zzVLvR5jUZ76RCsnSX8ZnSMXfLLbes17R/++03w14UoznCxIkTbSdhYscddzQ33XRTznP3U4pxabZr1y6nMahhGH7fWnPNNQPh06Vor7zyysHrgtp51NBTiIAIiIAIiIAIiIAIiIAIVC8BiXTVu/clvXK6CdbU1Ng5qlZT9q1CAKHW21NPPWU+/vhjg5MH5xcOIJxX3bp1ixSacPTQbbVr167msMMOMwsXLjSIU7jdKJhPwXtcRRtvvHHGSXB9znn11VcNNd2WWmop06pVK9O6dWuD4EGjCDpuEtOmTatVQD/76jIfgSCDMENQ8B9h7dlnnzXvv/++de/hhIMBDSWoURYXf/zxh53jDz/8YOjKyc8IfHS0jOrM6Y+zYMEC2/WSunv9+/e3Di7GmTJlim0IMGPGDFuDrHPnzma11VYrWZa87r7++mtDx1znpKNzLvfREksskZWDvzDqsd11113m9ddfD+rbwYC9QJAqlDPRF8hIfSYFOtegdhyvIQIBeP31189piFtuucWcffbZdc7htcm95ManMYcTmA8//HBzzjnn5HQdHSwCIiACIiACIiACIiACIlBZBCTSVdZ+VsxqEDa6d+9u1yORLvO28sEfgciJKlFHb7/99oaaVyussELwdLj2GmIddbKcmOaPk6nW29y5c81pp50WCGXh6/tuIZ5zQkVaNysdNOmkmSRoAEEq5CKLLFLrcOZ0wAEHBK4m/0mESkTATC4wUiJdvTHSGnfZZRdz6qmn1pkSLBCuEC+joiFZRjXMiGNKN9KDDjooUojiHIQn3HhxQadcXI9pdvl11/K7qiI+Dx06NMmtUesYxD3EaiKfGopck9cbQQ1B99qkFt2qq65q1llnHfscYiUdiQkE3OHDh+c8V50gAiIgAiIgAiIgAiIgAiJQOQQk0lXOXlbUSiTSJdvOWbNmJU5FpBkCDh8XPuNsV0OUwRGFQ86Pn3/+2TrtXL25bOPwPOJgvimoUePjQHr66adrPcV8SQslXdrvsMlBw4YNM/vtt1+t4xEoTzzxxNjpZ+tIiyCTVAyKS8FsaJas8ZhjjkmyhfYYGOOKDEdYoMPJyL3HPUJTBxcIlpMnT65zTyWeQMyBvkhHbT2afuQavkjH6wRRMZc444wzbC08J2ZS5JsgdXj11VcPusVefvnlpk+fPvY5xLzbbrstl8sU7VgclswVV6nKDxQNuy4kAiIgAiIgAiIgAiJQhQQk0lXhppfDkiXSJdslv8EBZyBKnHzyyaZp06bm888/t04nJ2CRsojjy8WkSZNMr1696lyIFLyddtrJPo5DzsVVV11l6PrpB49deumlwUOkeSL0cH2ue8cdd9h5+PHf//432eISHuU3OUAUueiii2yHV+eWe+2112wqr3MIIrjgjmrcuHFwBZ678cYbzZw5c6xjjnOZuzsHJ916660XOyOaALimAP5BNAJALCT11ndJ4agKp702NEvSc6+//nozb968WmIu9wNcqSv3+++/2zRg+JCyGb4fOAYXoRNGSXVmTJcu/Oabb1oHnuP6r3/9K6gfl3C7sx7m39dHHXVUrNsv00B+uuvUqVPNSiutlPW6/gHO3YkLk9fYP//5T/s0AjEiHennBA1JnGDcpk0bm7JeiuG/HyOsItYpREAEREAEREAEREAEREAE0icgkS59phoxBQIS6bJDfOGFF6zg4eLMM88Mulq6x+67777AqdOlSxfrhol6zj2G0ES6pgvSaEePHm1/RPyj3poL6rD5aZs4xEaMGFErLfTbb7+1ggS12lwUUqTj+ohK4Xj++efNIYccEjxMnTVSgDOF76YiXZHC/3GBmElatguEQFxR6667bvCY3zE03DG1VFi6ybZt2zYQ0nLpxkuTBYRjF7gvmzRpUgsb9xP3FYH4R1ppOP04+90ff4Tv5MMdGZV2nG18v3FEPjUU3b1DDUReM+51Sko0Apdzz/EaRtREtMRZSA3DUgy9H5firmhOIiACIiACIiACIiAClUhAIl0l7moFrEkfCrNv4vHHHx+kD5JSiAsn3OAAd9iQIUPsYCeccEItZ1y4uH1U3bl77rkn6Di5zz77BHW2GO+DDz6wAoMLmlbgHAoHaY40C3CiTFSKZPbVxh/hO+no5IlYGBW+6EaBftJkM4UvquHGW2WVVWIPp87do48+GqyRtE4aZ/iBQOOcjLj9qP/nolRYMh/ccv4+UqvOr2WYiRnOuFtvvdUegtB1ww031DmcLr+4C11ECXn1uR/8exbmvmiYdFy/g24+NRS537nvEbx5/XXo0MFe+uCDD7ZscV661xCcnNs0bQE76XqzHaf342yE9LwIiIAIFJ4A78X8H4p6q4VqvlT4VegKIiACIiAC2QhIpMtGSM83CAF9KMyMnZRDOmW6tMHzzz+/llPMnX3ZZZcFhenDqYWIcohFmQQVuqT26NHDHhNOl/UdS4iEpBlGBZ1SeZ6Iq2NWn5ssqUiHMOdEo+OOO85QNyxTOKGFY3B7LbfccrGH+3OgM2pUGjGdZ6+++mo7Rr9+/WzTABelwpL5+J2V+RkB0U8NzsQMxxjuMAK+cA4HnYDXWmut4OHx48cHnZzrcx+4c32nXtxeZLtOy5Ytg0PyEc7c+TQjufjiiwPBltp8pLVed911wWvBT63Nx7WXbS1pPK/34zQoagwREAERqB+Bmpoa+zs6399t9bu6zhYBERABESgWAYl0xSKt6+REQB8KM+P66quvDKl0LuI64F5wwQVWECBw7zjBjZ+pJUcdNCLOcYQ4hQONIN3T7yDrpzbiGIqqycZ5P/30kxUmiEKk9CUV6UiFdU0EqBXnHIZxpH031XvvvZexwcG+++5rqF1G0Bxgyy23rDOs72oMNzQoFZZM+uuvvzabbbZZMP9cRCqfGYLkXnvtFYnXF0AzuR9zetP4/4Pploo47e5xhLJcYuHChUGacj73K7X9NthgA3tJVxPPuTh5DfG6pRadE7bpYs37HRFVqzCXuRfqWL0fF4qsxhUBERCB5ATcF0CUTOjbt2/yE3WkCIiACIhAWRGQSFdW21U9k8VR0qlTJ7vgOAGqemjUXSmF+UnHdBFXN2zw4MEGEYRAsCPdzoXvLDvrrLMiO3t++eWXQaoe5/mdWRGlEKcIhAfSDKMCtx81zohCO+ky1Zrzmzsk+Rbar8v29ttvZ0wt8WuY3X///WaTTTapg+KBBx6wdf2IcIfXUmHJ3Pw9z3W/fGY0jMAlFg662K6//vrBw6THbrvttqm9nGmW4roYx9UozHSx2bNnW9cokckhGjcGrxEccwT18KiL56c6I1Aierl7wE9bf+SRRwKBLzUgKQwkkS4FiBpCBERABOpJQCJdPQHqdBEQAREoEwIS6cpko6pxmr179zbTp083o0aNUjfB0A3wxhtvGGrEuYiqmUZtMcQj12mT5gbUpXPh1w87/fTTDWJBOHwXHM/59cn82mKIOTwXronHOWFRJhdnVpL73nfSZRJ8/FRMXG2ug23cNXxXWLaadNtss01QVwyXlO9Ec+P7qcPhTp6lwpK51kek8x2F4UYjjoMv+PAYnXb99Ncke57pmKOPPtqQPkzceeedho7DucQ777xj9thjD3tKJvE5bkxq7LmOra72oO/idOfRARYRnc6vNBkh6CjcsWPHXKZblGMl0hUFsy4iAiIgAhkJSKTTDSICIiAC1UFAIl117LNWWWEEZsyYUevDfJQ45Xd2Zfku9c6h8F12mWq0+fW5aE7hUlcZx3dORTWe4BiaJeAkcvHuu++apZdeOrUdoQHE008/bceLE2W4pu/qimty4U/KF+kmT56cUSj2m0zEufn81OEoh1opsGT94VTqXBo7+F1ucZM5R5vP1U9H5fFPP/001e6ue++9t3nzzTftJUkjbteuXU73GveSayoSdjwmGYjXyDHHHGMPdd2Sn3zySYMo5wfp1qRdU7Nu+PDh9inSz5l/qYVEulLbEc1HBESgGglIpKvGXdeaRUAEqpGARLpq3HWtuewJUHyfuleucUS48yruuc6dOwfPs+Bwt02/qQRpsKTDRoXvEgunDyIuIDIQ1O+iHtu6664bDOOncboHn3jiiVrH1HczED8QQQgaMtDNc5FFFgmGJX0R0QWhjogTj8Lz8Nedbc7777+/wW1HXHnllbVcjm5cP42Sx6ZMmWKZuSgFlswlfG+FG45k2q/HH3/cisEEQiRiaNOmTYNTfvvtN+sycyIaLjeE1TTDFztpZuKalkRdA6cozs7VVlst6GB71113GZylBIKZq9sYdT6s6OI6f/58s95669lD/K7JpIDjxvNTYN04TsxFyHPdXnNhnSazbGP5Ih1djF36erbz9LwIiIAIiEB6BCTSpcdSI4mACIhAKROQSFfKu6O5iUAGAn63UA4jbQ6x7pVXXrEigxPw3BDhIvh+F8zddtvNIMBFhZ9OSh075zLiWFJZcZEhVBAIM4xF+iJdQencGY64WmX5brYv0jEGzikcUE2aNDEfffSRdVORTuoiqu4XoiZpnnTNdUFhZnfev//971opmYgUjO+C1OyJEyfaH8OM3DEIVOuss07sPEqBpZvcYYcdZtNQ3Z4ee+yxpmvXrmallVayzjfcZvzNPbfCCisEa4IfTUQ+/PBD+9jaa69tBg0aZPeEjnQ0k0DIdZFPOmqm+8TvJMxxvA6aNWtmm5d89913Zu7cuXZP2WvEOXffNm/e3Dz//PM2Xdt3+iHwUVOOcRHi5s2bZ//MmjXLpuI74Zdr0YiFJhX++dwTiHfhved4mrDQSMJvGkJjFyfY5ft6KMR57F3//v1tXcahQ4cW4hIaUwREQAREIAsBiXS6RURABESgOghIpKuOfdYqK5AAogGuMF+ACi8T9xxuIhc42xBaiIcffjioQ5ep9hbF752wglPtlFNOqXUZREHS9sKioDsI4W7JJZcM5pm2W8gXyLJtc1TtPVxyPXv2zHZqredpDEGDCBd+swL4wCkq/BRaHFsdOnQoKZZuMjjdkqRd0i0XEdePF154wVD/L1uEnZ3Zjk/y/Jw5c8zmm2+e5NA6x3Af4/qjqQgut1wDYRMxl7RvatERfi1D323Ja4JmJIsuuqj9G9crsf322+d17VznquNFQAREQATKj4BEuvLbM81YBERABPIhIJEuH2o6RwRKhABpdDjJXHMIf1oIJYhHfmoaHUY33nhje5jfITZT2iHOM2rWEa4Qfnj5pHIi5jn3lXt+ww03tOmw1DVjLkTa7imaQFDfi8DZRX2+zz//vNYUcRGS3osIEg5frEy6rWFeiJisn6D+Him3UeELQKTo+s46d3xDsvTnjMPrjDPOyCi+wq5Vq1Z1lsp+4wqLE25JiYXTUkstlRR5ouPCTUqyncR9wfxxXrqmKtddd11s6nfUeLjtWrdubfr27WtTa6lfSPo47kEYuvDH7d69e5AmTsosIjH3Q1yzjWzr0PMiIAIiIAKVT0AiXeXvsVYoAiIgAhCQSKf7QATKnACpaIglpM+RYoroQJfNTp062dps1NQiFQ9BgvQ7P02TbpKk/ZHKGFe7i1Q9nEU49xATSHmLC1IKcQaRHohr7G9/+1twKM0umA/1v9KMhQsX2s6yrI80W1IuSUdEwCQ1EZGS/9g2atQo8rILFiwwiJdwJN2ROeJwcv/mb352jzVu3NhsscUWtZpfIEbRhZhrkA7sp4D6F6UpAzXLVl11VStiZYqGYBmez7fffmvoVkvHU/aPhh+4zRCgaMTh19QLn0tqKbXMcNbh9iSllHsTFyL1FAsVH3/8sRWF2a/FF1/csF/8wc257LLLBn+4j5dYYok60+B+IJ3X3Q8cw7mMgQMOBsstt5wdh7+j7ivSfUll5RwXiHG81ri/WrRoUatuIuIi6bOItsxbIQIiIAIiIAJhAnwhSfdy/r+h2qC6P0RABESgcglIpKvcvdXKRCAggODgxAphEQEREAEREAEREAEREAEREAEREAERKD0CEulKb080o/8nwLeFX3zxRc71wgRQBERABERABERABERABERABERABERABMqNgES6ctuxKpkvzq+amhq72jFjxpj27dtXycq1TBEQAREQAREQAREQAREQAREQAREQgWokIJGuGne9DNZMLSuKq0ukK4PN0hRFQAREQAREQAREQAREQAREQAREQATqTUAiXb0RaoBCEJBIVwiqGlMEREAEcieAs/nyyy+3DS9oHqMQAREQAREQAREQAREQAREoDAGJdIXhqlHrSUAiXT0B6nQREAERSImA/348efJkK9YpREAEREAEREAEREAEREAE0icgkS59phoxBQIS6VKAqCFEQAREIAUCej9OAaKGEAEREAEREAEREAEREIEEBCTSJYCkQ4pPQB8Ki89cVxQBERCBKAJ6P9Z9IQIiIAINT4D34mnTppmuXbua5ZdfvuEnpBmIgAiIgAgUhIBEuoJg1aD1JaAPhfUlqPNFQAREIB0Cej9Oh6NGEQEREIH6EKipqTHUCB04cKDp1atXfYbSuSIgAiIgAiVMQCJdCW9ONU9NHwqrefe1dhEQgVIioPfjUtoNzUUERKBaCbRs2dIuvU+fPqZv377VikHrFgEREIGKJyCRruK3uDwXiJ2/U6dOdvJjxowx7du3L8+FaNYiIAIiUOYEJNKV+QZq+iIgAhVBQCJdRWyjFiECIiACWQlIpMuKSAc0FIHevXub6dOnm1GjRqmbYENtgq4rAiJQ9QQk0lX9LSAAIiACJUBAIl0JbIKmIAIiIAJFICCRrgiQdQkREAEREAERKFcCEunKdec0bxEQgUoiIJGuknZTaxEBERCBeAIS6XR3iIAIiIAIiIAIxBLwRbrJkyfL2ax7RQREQAQagIBEugaArkuKgAiIQAMQkEjXANB1SREQAREQAREoFwJ0E+zfv78V5wYNGlQu09Y8RUAERKCiCEikq6jt1GJEQAREIJaARDrdHCIgAiIgAiIgAiIgAiIgAiJQwgQk0pXw5mhqIiACIpAiAYl0KcLUUCIgAiIgAiIgAiIgAiIgAiKQNgGJdGkT1XgiIAIiUJoEJNKV5r5oViIgAiIgAiIgAiIgAiIgAiJgCQwZMsRMmDDBjBo1yrRt21ZUREAEREAEKpSARLoK3VgtSwREQAREQAREQAREQAREQAREQAREQAREoHwISKQrn72qupmOGzfOULC8Z8+eVbd2LVgEREAEREAEREAEREAEREAEREAERKC6CEikq679LpvVzpgxw3Ts2NHOd8yYMaZ9+/ZlM3dNVAREQAREQAREQAREQAREQAREQAREQARyJSCRLldiOr4oBF566SXTvXt3iXRFoa2LiIAIiIAIiIAIiIAIiIAIiIAIiIAINDQBiXQNvQO6fiQBiXS6MURABESgNAhQduDyyy83yy+/vOnTp09pTEqzEAEREAEREAEREAEREIEKJCCRrgI3tRKWJJGuEnZRaxABEagEAv778eTJk02LFi0qYVlagwiIgAiIgAiIgAiIgAiUHAGJdCW3JZoQBCTS6T4QAREQgdIgoPfj0tgHzUIEREAEREAEREAERKDyCUikq/w9LssV6kNhWW6bJi0CIlCBBPR+XIGbqiWJgAiUHYEJEyaYd9991/Ts2dOWH1CIgAiIgAhUJgGJdJW5r2W/Kn0oLPst1AJEQAQqhIDejytkI7UMERCBsiZQU1NjqBE6cOBA06tXr7JeiyYvAiIgAiIQT0Aine6OkiSgD4UluS2alAiIQBUS0PtxFW66liwCIlByBFq2bGnnRAOfvn37ltz8NCEREAEREIF0CEikS4ejRkmZwLRp00ynTp3sqGPGjDHt27dP+QoaTgREQAREIAkBiXRJKOkYERABESgsAYl0heWr0UVABESgVAhIpCuVndA86hDo3bu3mT59uhk1apS6Cer+EAEREIEGIiCRroHA67IiIAIi4BGQSKfbQQREQASqg4BEuurYZ61SBERABERABPIiIJEuL2w6SQREQARSJSCRLlWcGkwEREAESpaARLqS3RpNTAREQAREQAQanoAv0j366KOmbdu2DT8pzUAEREAEqoyARLoq23AtVwREoGoJSKSr2q3XwkVABERABEQgOwG6CXbr1s2sscYaZuTIkdlP0BEiIAIiIAKpE5BIlzpSDSgCIiACJUlAIl1JbosmJQIiIAIiIAIiIAIiIAIiIAJ/EZBIpztBBERABKqDgES66thnrVIEREAEREAEREAEREAERKBMCUikK9ON07RFQAREIEcCEulyBKbDRUAEREAEREAEREAEREAERKCYBPr3729efPFFM2rUKNUGLSZ4XUsEREAEikxAIl2RgetyIiACIiACIiACIiACIiACIiACIiACIiACIhAmIJFO90TJEqCj4IwZM0zXrl1Ldo6amAiIgAiIgAiIgAiIgAiIgAiIgAiIgAikQUAiXRoUNUbqBOgmWFNTY8cdM2aMad++ferX0IAiIAIiIALxBHgfvvzyy83YsWPN8ssvb3r16mV69uwpZCIgAiIgAiIgAiIgAiIgAgUiIJGuQGA1bP0I4KLr3r27RLr6YdTZIiACIpAXAd6Dj+rd28z//vta57dt29aMHDnStGjRIq9xdZIIiIAIiIAIiIAIiIAIiEA8AYl0ujtKkoBEupLcFk1KBESgCgjgnBswYIBdadutdjWdjxtk5s6aYcZfO9jM/ORd66rD4YxgpxABERABERABERABERABEUiPgES69FhqpBQJSKRLEaaGEgEREIGEBEhvHTZsmD2687EDTcf9egVn/vLD9+aha4eYKY+Ps0LdwIEDzQEHHJBwZB0mAiIgAiIgAiIgAiIgAiKQjYBEumyE9HyDEJBI1yDYdVEREIEqJoB7Dhcd0XXApWazXaMFuLGX9LdCHXHppZdKqKvie0ZLFwEREAEREAEREAERSJeARLp0eWq0lAhIpEsJpIYRAREQgQQEkgp0bihfqFNznwSAdYgIiIAI1JPAtGnTDH923XVX62ZWiIAIiIAIVCYBiXSVua9lvyqJdGW/hVpAAxB47bXXzKOPPmoWLFhgfv31V/PLL7+Yn3/+2TRq1MgceeSRpkOHDg0wq+Jfcvr06eauu+4ydCf97bffLIcff/zR/Pnnn2abbbYxhx12WNZJ3XfffWbq1Knm999/tyx/+uknO86SSy5p/vWvf5nmzZtnHaNcDshVoHPrGn/tEDP5vhtVo65cNlrzFAERKGsCHTt2NDNmzJCDuax3UZMXAREQgewEJNJlZ6QjGoCARLriQJ89e7a9UNOmTfO6IALIxx9/bNZZZx2z2GKL5TUGJ82fP9/88MMPplmzZlZQ8gORZM6cOWaRRRYxq6yyiv1bEU0AAerzzz+PfLJ9+/a22H81xD//+U9z2223xS6VezbT/Tpz5kwDr7jo37+/OfnkkysCZb4CnVu8c9Th6pg8ebLcHRVxV2gRIiACpUigZcuWdlp9+vQxffv2LcUpak4iIAIiIAIpEJBIlwJEDZE+Aez8nTp1sgMrlSp9voz49NNPm8MPP7xejPfee2/z5ptvmi222CKoZZXrbC+77DJzxRVX2NP22Wcfc+WVVwZD4AIjrcMJT9ttt5255ZZbcr1E4uPvvfdeKzruv//+Zu211058XqkceMIJJ5jx48dHTmfPPfc011xzTalMtaDzuPXWW63bLSqWWWYZmy6UKXDMbbXVVuabb76JPOzf//53IjdeQReZwuD1FejcFK48dnfb9ZVur7xfKw0rhc3RECIgAiIQIiCRTreECIiACFQHAYl01bHPZbnK3Xff3dr6H3vsMdOiRYuyXEMpT/rss88OBK98vpXFhYc45+K9994zSy21VE5LDo/Bya+//rpp0qSJHccXEt3AH374oVliiSVyuk6SgxEE119/fXsoQs4777xTx9WXZJyGPuazzz4zf/zxh537gw8+aBBBie7du5uLL764oadXtOtzb+HOhMOXX35pDjnkEHtt0lRx6maLhQsXWnGY83FvDho0yN6PBB1Qu3Tpkm2Ikn4+LYGORdL1dcSAboFQR8q1QgREQAREIF0CEunS5anRREAERKBUCUikK9Wd0bxEoMAEfJGOtAmEulwiLLB98MEHpnHjxrkMESnC4YLadttt7Tg47JzI5AZ+8cUXzWqrrZbTdZIcTM0ynEAu8hEdk1ynmMfgajrttNPsJXFNnnPOOcW8fMlc65NPPjE77LCDnQ8OyaeeeirnufH6oE4dce2115o99tgj5zFK5YQ0BTq3JoS6i3psZX75cb7t9krXV4UIiIAIiEB6BCTSpcdSI4mACIhAKROQSFfKu6O5iUABCeAMGj16tL0CH9pPOumknK721VdfmX/84x/BOdnqfEUNTuoqYqEfzKtnz572IZodPPnkk7Wef+SRR8wGG2yQ01yTHIz7rFWrVsGhlSDSUZeN+mzEMcccY84666wkKCrumPfff9+mTRNt2rSx7txcw08lvvHGG81OO+2U6xAlcXwhBDq3sJkfT7OOOgl1JbHVmoQIiECFEZBIV2EbquWIgAiIQAwBiXS6NUSgSglQV2vUqFF29dTv6t27d04kvv32W7PJJpsE5/z3v//N6XwOPv/88831119f6zw6bzI3YtNNN7V1wVZeeeWgPtjtt99utt5665yvleQE9x9gjs1HdAxfg9pmpObm2+yCbqSMkWsasZvHzTffbAYOHGh/POWUU0y/fv2SYCjIMaQT05Bh9dVXz9lxWd8JkbrsnG8Iy/fcc0/OQx599NFmwoQJ9rxC3oM5TyyHEwop0LlpfPLmS2bkErHutQAAIABJREFUqd3tj7jpcNUpREAEREAE6k9AIl39GWoEERABESgHAhLpymGXNEcRKAABXyA799xzTY8ePXK6ynfffWc22mgje06SYvxRgx9//PHm4YcfrvWUaw4xd+5cs/HGG9vndtttt0AgofkBTRDSDLrHku66/fbbB8O+9dZbVmBbfPHFc+pc+/zzzxtqcr388suG+nkEtfuosXjEEUeYRRddNOPU6XSLw3HKlCl2DOa15pprWkEUoY1Ouklj5MiRhr0l8nFLJr1O3HEIrKQsv/LKK+bdd98NDiP19vTTT7f3TaZApMT1Rnoqoilj0JQAnnRf7datW6K9obkJTU6IfLvc+q7Ou+++22y55Zb1xVPU84sh0LkFvT5xrBl36QD7o4S6om6zLiYCIlDBBCTSVfDmamkiIAIi4BGQSKfbQQSqlMAFF1xgrrvuurw/SPsiHU43RKVcY9999zVTp061ogtCDuEK+9NAYr/99rOPIU65DrCIi64JQK7Xizo+KuU26jgEpSWXXNIMGTLE7LXXXnUO+f33321nWpoKxAUCEcc0bdo08hBEPRxb1FCLi0suucSKU0mC2mkXXnihPRRRDFG0WEGTBZx7cR1St9lmGytGLrbYYpFTQpQj9fm5556LnTKiKjxXWGGFjMvy7yWuSxpwroHD85lnnrGn0QV4s802y3WIBju+mAKdW+Tke28w4687x4qq1Eb06z02GAhdWAREQATKmIBEujLePE1dBERABHIgIJEuB1g6VAQqiQDiDSIOcdVVVwVOo6Rr/P77701NTY09HKdXJjElbkxEK1Ig99lnHzNt2rTAefbRRx+Z8ePHB80sEL5cYwsaIVAfLK0YPHiwuemmmxIPx1wRhsLhpw/zHGIQ3WJJtXzhhReCw6mNhsMtHHQg7dChQ/AwwmenTp0MXUYnTZpUS+xKWpePfXUF/PNJaU4MJXQg7siwIEgtuHnz5tn9dhHn4Jw1a1Zip5pzXmaaKwKwS7vccccdc9pvN+5BBx0U7OMDDzwQuDzzZVSs8xpCoHNrG3tJfzPl8XES6oq12bqOCIhARROgLAnNsyhVwv+fFCIgAiIgApVJQCJdZe6rViUCWQkgkDixiL9dYf2sJ/7/AQgu7dq1sz/9/e9/t0JSLkEq41prrWVPIZWQRhQIcwSCH0KIE5juv/9+g+uO4D+pCE5pBa41nFXU2HPdOxm7a9euBnec+0NjCWrDkarp0nDdHGbMmGE6duwYTOnMM880xx57bPDz2LFjbbqpiyiRhwYPzuGFm5BjnOPu66+/NkcddZR1HRJJhSbEzWHDhtlz/IYcabGLGof0XARK56DbcMMNrQhMV1Xq0lEbzjkF45o40MTkwQcfDIY/9NBDzcknn2x5fP7557bZCE49AhcmfDMFIikiGxEnkmZjsv/++5vXXnvNHoYIybpKPRpSoHNsnFDXokULmwaOs04hAiIgAiIgAiIgAiIgAiIQTUAine6MkiWAswrxI1fxqGQXVGITO+ecc8wNN9xgZ3XrrbeabbfdNqcZIsLQ2IFArPNFlSQDUXvNCR19+/a1pzhBCdFl3LhxNk0OweqOO+4wO+ywgz0GR5QT75JcJ+kxuPdcx85cnYG+wBYnPCEuTpw40U6nc+fOZvjw4cHUwiJflGjqNz/gRMZab731Mi7vsssuC9KE2W8ExkIHe4MoR5AizLf+fjqqXycvqpahL6gxRljw5DHEVOes7NKlS8YUY46nTqBLkaa+4YgRI3LG4It0SZ2MOV8kxRNKQaBjOb/88L3t+Drzk3dtyiuvaQl1KW60hhIBERABERABERABEagoAhLpKmo7K2cxfiolH+pk609/b/0P8fkUwqebqxP28inGP3369KBLKy6vJk2aGBxUBOmkuOeefPJJQzfOq6++OrgHkrrIciXm1y2LE9rixsQ5hsOLoJtqr1696hxKZ1DqzRG4ymiG4OKhhx4yJ554ov0R4eqNN96wTSvCsfPOOwcpwXTFpRlFpvAFM9JxqatWyPjtt99qNbbAyYeI5gduuu7duxuaOUSl4PrNRHBo0jgiXLfuxhtvtLUBCVKfSYHOFM8++2zQGCVfkc7VT+Q6pS7S+c7NrgMuNZvt2rAdViXUFfJVp7FFQAREQAREQAREQAQqiYBEukrazQpay0svvWQ/yBMS6Qqzsb6zizRTV18u6dV8ZxfikXPlJT2f7qmuAQNiEvXbcJgRZ5xxhk19/c9//mMfo1mE6ySbj2svyZwQBEm7JRAG77nnniSnmbAwFddUwO8wysCfffaZadSokb0GIiQNIYhMNdb8DqNxYqA/6Ysvvjhw7BVDpPOFW+ZBN9all166DkdSiEkfpnOuHzyGu5KUWSKuSYjvEExSa4/UWOcizFekozsse0iUskhXagKd219fqMt3DxK9IHWQCIiACIiACIiACIiACJQxAYl0Zbx5lTx1iXSF313SRl1HVbpWuvpwSa/s7xH124YOHZr0VHucL5yQAknTBJf+2qNHDyuEkFJLLTZSHtdZZx17nuv+mtPFEhyMY+uYY46xR9I19Oabb05wlrEOOpx0Ll5++WXTrFmzOueGU1oRKV0a6KmnnmpwMxKsnXqBUYFjDNGaoOYdXDKF3xwE59kRRxyRaE35HuTvaT51CqlLiEDqIk6g9zsTxzWf8NfgzyvfmnR77rmnFY2JUhXpKBHQrXt3M//7700pOOjC99Hc2TPMlcfubn75cb5NV3Zp7vnebzpPBERABERABERABERABCqNgES6StvRClmPRLrCb6SfojllyhRDN9Fcwu/gSXonzq5cwnf8UH9u8803tzXuEOa22mqroJOmc0pRz8o5rHBspR3U1HPptggy11xzTaJLfPjhhwYnoQvSZkndDYd/T/McggqprYTfKAG3HB1no8IXVkmPRdzLFBdddFGwDpotIHgWMug4h2OP6NatW+AOTHpNGkq42oOcEyd4+h15EewOPvjgjJfwRbp8XJ8M7jvpSE92zs6kayvGcXQD5r7aqUcfs3OPv+o8llrM/HiaufK4TnZaNJLgda0QAREQAREQAREQAREQARH4i4BEOt0JJUlAIl3ht6Vly5bBRT744APTuHHjnC6K08wJczhiXCH/pIMggiEiEaSa4pQjJdF17XTjuNprvqj4/vvvmyWXXDLppRIdRzdVOogS++yzj62LlyR++uknQw07F7fffntQa88//4orrjCkaRIIogijLnAhuuttsskmth5fOKjlRkqwC1KEEe0yhV+TjuYWriZeknXlcwz3g3MgZhIb48amFh/sXdBNdZVVVql1OKmyCG2uQyzuQurSZQq/Jl0uLkl/TL8mHfvDPpVSONG7+dptzMnXPVZKU6szl8n33mDGX3dO3p12S3pxmpwIiIAIiIAIiIAIiIAI1IOARLp6wNOphSMgka5wbBn5hx9+MBtssEFwkXycab5LK0ldsPCKfDfU1KlTzUorrWT8NEZ3vEst9J1MdAxdbbXVUoWEq4cUUiLXxhE0zpg5c6Y9l3p6xx13XJ25+S64cMql362UEz/++OM6zRLCTjycjC49OA4E3XJp3pBpXmlC9IXITM1E5syZYxBF4bz11lsHUwinBEd1HQ6zwh2ISzBTTJ48OXDbZar5l2kMv7trXN3BNFnmOpbb61J20bk1kfZ6cY+OZrnllgtSiHNdr44XAREQgWojgFOaP/wfQl2yq233tV4REIFqIiCRrpp2u4zWKpGusJuFCESXVIKUS/7Tlym+/fZb8+WXX1onl+u0iesMoYXIlnJIcwVqt+F+c+IaghjCGIEratFFFzV+Cqybz9tvv23/M+o3TSA1lQYSaQZNDvxuqaxt4403TnQJ6qJRV4+gphq11PyOpKTwksrrgjRV182VxxCtSPd1gRsNx5cfNFHAVegiiZvwqquuMrjpCLr5unTeRIvK4yC/rh+n87PvMuSxhQsXWsHM1UP0U0f//PNPKx67tOawo5H7hEYi7nnGS5K+Stos6bdEPp2IOY9GNrwvEfl0Q84DZ06nBE66ddqak6/963VVqjHp1mHmiVsvl5OuVDdI8xIBEShJAh07djR8mZXESV+SC9CkREAEREAEEhGQSJcIkw4qNgGJdIUlHnZl4bZCPPnll1/M3Llz7R+K+E+fPt189NFHgSiCG8yJPr4zDOEEsWTBggXmu+++M/PmzbO15WbNmmXHcKmJrOqpp54ya6+9tk3VRKjxRcJwB1Q/LZR0zdtuu82CoRuq6wybFinWv+666wbDMUeEROrTEYiFNNhATAzXgmOdW265ZXAu3StJLUWgoosrKZmu6QDrxdm14oor1pq67yzkCTjTTGOppZaynW79mn9R6cUIR8yPPSTonApf9oFA1CRleIkllrACIn8jWOXa1TcTb8QzxEYnorF/uNy4Lnyp3zd8+PBA7GKscNMSutyyvy7Yd8Q61nL66afXEug4Jpw6zHGIpNyDBPv1xRdfBPw5/sADD6zFoVWrVmaXXXaxx8OPOSJkcz8vssgiliXORRfcE6Rn8zh/6GCLwNu0adO0bse8xnFC4ma7HmAbR5Ri+DXpeB20aNGiFKepOYmACIhAyRFwZUrUeKfktkYTEgEREIFUCUikSxWnBkuLAM4uiqATcR0e07pWNY5DCmlUSmY2FmuuuaZ57rnn7GEU+PfFt2znuuepRYfIceihh9qxEMMQ7ohwfTfErhEjRtjnbrjhBnPOOefYf5911llBJ9ak101y3OjRo82gQYOyHjpx4kSz3nrr1ToOYefiiy/Oem5cA4fZs2dbMcqlzcYNhMgEN9d0guPC9eqyTuL/DyhEp9y77rrLimlJAlEpzGz+/PmGlFQnLkaNgyA8adKk4CmXLs0Dflpqkjm4Y1544QWz+uqr24YlBx10UC6n2mNxB+IobcjgffOAbt3MD/Pnl2R3VwS6Ead2N7/88L0VnWk4oxABERABEUhGQCJdMk46SgREQATKnYBEunLfwQqePx/gcWHhEJLbIt2NRtSgEH7SQMxp3bq16dGjR+A4Ouyww6wLKkkgKOFWotg+rjLSV3HvUUcr3KXUH5djunTpYi+BM4oUXcSbQqUbkm554YUXmuuuuy52WdSBIxXWT2d1B1NDjfp8cYEgRdplo0aNIg8h7ZW0Xue6Cx+EeMX8ourx4eQiZTeXIDX3nnvuyeWUrMfC8JZbbsna7ZdmD/369YvkiPsQDlEiMAIaQqffFdRPTfZTj7NO9v8P8N2NpHUjAvoptUnGyad5SpJxcz1mwoQJQYMQ3HS46kohfIGua9euhmYpChEQAREQgeQEJNIlZ6UjRUAERKCcCUikK+fd09xFIE8CCCnU6aJOHGITKXvUi6PDK+mVyy67bPCH4u5RghRiGV0zqTfH+ZzLH8Yh/Y/zGIe/+TkczAHnD2KLL1qRFok4QyOJcGdPauPR9AJHXyGDbrfUy0Ms+/777+06+M8xNeoQw0gVjQuacJBO/Oqrr1pnIOIkbkFSV5M0uyDdkq6mNMcgPRTnHKmViKSkjcYJfOwDAtMff/xhYMsf/u3+uJ/pjspj7BNuwLjx6ssXwZCuvayFlGnWgVMNhnvssYf9d6aAOymmuAbZDzgiLOOwJQXV1dtjXJyNTZo0CYbDjUiqKuF4uHX7XHiMsai16O8p+0a6t+MYZse4bjzG59ql9EWCX9uxFIQ6nHM46BDqcm3KUt/7UOeLgAiIQKUQkEhXKTupdYiACIhAZgIS6XSHiIAIiIAIlCUBhDwnDpflAgo46VIR6sICHS5YdSUs4MZraBEQgYolIJGuYrdWCxMBERCBWgQk0umGEAEREAEREIEKJOALdQ3RTEICXQXeVFqSCIhAgxGQSNdg6HVhERABESgqAYl0RcWti4mACIiACIhA8QiEhbrOxw40Sy67fMEnIIGu4Ih1AREQgSojIJGuyjZcyxUBEahaAhLpqnbrtXAREAEREIFqIEDtRxqW0Dm3+TptzdGXjCmoUCeBrhruKq1RBESg2AQk0hWbuK4nAiIgAg1DQCJdw3DXVUVABERABESgaAQQ6o466ijzxRdfWKGux+CRZsWmLVK/vgS61JFqQBEQARGwBHr37m2bSlHb0+9wLjwiIAIiIAKVRUAiXWXtp1YjAiIgAiIgApEEaLSBo47Ou6S84qhDsEsrJNClRVLjiIAIiIAIiIAIiIAIVCsBiXTVuvNlsO4JEyZY10fPnj3LYLaaogiIgAiUPgGEOtwYL730khXqDhhwqWm71W71nrgEunoj1AAiIAIiIAIiIAIiIAIiYCTS6SYoSQJ8kKypqbFzGzNmjGnfvn1JzlOTEgEREIFyJNC/f38zbtw4O/WuAy41dH/NNyTQ5UtO54mACIiACIiACIiACIhAbQIS6XRHlCQBXB7du3eXSFeSu6NJiYAIVAKBYcOGmcsvv9wupeN+vQydX3ONmR9PMyNO7W4Q6tq0aWNrJS2/fOG7x+Y6Tx0vAiIgAiIgAiIgAiIgAuVAQCJdOexSFc5RIl0VbrqWLAIiUHQCY8eONQMGDLDXxU2Hqy5pSKBLSkrHiYAIiIAIiIAIiIAIiEAyAhLpknHSUUUmIJGuyMB1OREQgaolQP1P0l/nz59v1m7X3vQYNNLWq8sUEuiq9nbRwkVABERABERABERABApIQCJdAeFq6PwJSKTLn53OFAEREIFcCUybNs12fkWoo+MrnV/jhDoJdLnS1fEiIAIiIAIiIAIiIAIikIyARLpknHRUkQlIpCsycF1OBESg6gkg1B111FG2q3acUCeBrupvEwEQARFoIAK4nt99913Ts2dP1f5soD3QZUVABESgGAQk0hWDsq6RMwGJdDkj0wkiIAIiUG8CdNbGUccHwRWbtjA9Bo+0gh3x+sSxZvx159gmEV27djVDhw6t9/U0gAiIgAiIQDICNTU1hvfogQMHml69eiU7SUeJgAiIgAiUHQGJdGW3ZdUx4WoX6b777juz7777mp9//tlcf/31pl27dtWx8fVY5a233mouuOACc8ABB5ghQ4bUYySdKgLVTYAPgb179za8DxM0lJg7e7r55M2/fsbFMWjQoOqGpNWLgAiIQJEJtGzZ0l6xT58+pm/fvkW+ui4nAiIgAiJQLAIS6YpFWtfJiQBpV506dbLnjBkzxrRv3z6n88v94Mcff9ymnRF8W8q3pop4An/88YfZcMMNzY8//mgP+uyzz0yjRo2ETAREoB4Ehg0bZkbdcIP5Yf58O0qjRRYx/fv1MyeddFI9RtWpIiACIiAC+RCQSJcPNZ0jAiIgAuVHQCJd+e1Z1cwYJ8f06dPNqFGjTIsWLapm3Sz0nnvuMf369bNrPuigg8yFF15YVevPdbGIc23b/pWSR/z3v//NdQgdLwINQmDq1KnmgQceMLvttpvp0KFDg8wh00VnzJhhRowYYW6++WZ7WDV+aVJym6IJiYAIVCUBiXRVue1atAiIQBUSkEhXhZuuJZc+gbvvvtuceuqpdqKHHnqoOe+880p/0g04w2+++cZsuummdgbLLLOMwYmpEIFyILD//vub1157zU510qRJ5u9//3vJTbvayw+U3IZoQiIgAlVJQCJdVW67Fi0CIlCFBCTSVeGma8mlT+COO+4wZ555pp3o4Ycfbs4555zSn3QDznDmzJlBSvTKK69spkyZ0oCz0aVFIDmBvffe27z55pv2hNtvv91svfXWyU8u0pG+SPfoo4/Wcq0WaQq6jAiIgAhUPQGJdFV/CwiACIhAlRCQSFclG61llhcBmiD861//kkiXcNtIi3bixpprrmmee+65hGfqMBFoWAI4Zd39WqoiHSmv1MhcY401zMiRIxsWmK4uAiIgAlVKQCJdlW68li0CIlB1BCTSVd2Wa8HlQOCWW24xZ599dqRI9+eff1ZEU4Q01/Hpp5+a7bff3vJq06aNeeyxx4qyzT/99JNZeumli3KtUr9ImvvZkGst9jqOPvpoM2HCBLtk0ty33HLLhly+ri0CIiACIlCiBCTSlejGaFoiIAIikDIBiXQpA9VwIpAGgRtvvNEMGTLEDoXTBpfYfffdZz788EPzySefGFI6eWyHHXYw++67byLR7u2337YNKT766CNbs+2XX36xgsBmm21mDjnkELPiiitmnTpdU+k8y/nffvutmTt3rpkzZ4759ddfzUMPPWRWX3312DEQPyiQ//zzz5s33njDrmXttdc2e+65p3Xp/O1vf8t4/Z9//tk6jl5//XXzwQcfmFVWWcWstdZaZuONNzZNmjQxu+yyiz2/Xbt25sEHH8y6lnwOoIssQsrkyZPNq6++akizZS+4Zo8ePcyOO+4YOywOJBh17drVHHbYYWbhwoXmP//5j3n55ZfNO++8Y1mwn6ynUME+nXvuuebdd981AwYMqCUIIXS+9dZbdj+p8UdHZSd8Rs2nvvvJmMyHRgTsKfcDPHBCbrTRRmaTTTax9+VSSy1V6/LfffedvY/gvscee8Te+08++aT5/PPPTefOne39ERcIrbfddptNkea+ZE/Zz4MPPtju1WKLLZZ1O7gvSFnlmjQt4bXx9ddfW5atWrUyY8eONYssskitcb7//nt7DJ2bnZOO5gxbbLGFWWKJJRJdN+vEdIAIiIAIiEDFEJBIVzFbqYWIgAiIQEYCEul0g4hACRJA0EFMSRKIEBdddJFZdtllIw9H1Bg6dGjQnTHqIISRG264wbRu3TpyDIQ5roGQEhdnnXWWOeaYYyKf/vLLL80ZZ5xhnnnmmcjnafZw5513WnEkKhCVjj/+eCtQRgXn0+GVQFxC+Ek74EjHXYr7x8URRxxh/vnPf1qRxQ/Eze222y54CLHuwAMPDObsH3vNNddY4bIQgbh18skn26G5xvDhw63gdcUVV9RhC1OE3UUXXbTOVOq7nwz49NNPW7coQlpccF9ed911ZoMNNggOOf/88831119vfyYtfNttt61z+qxZswIBknXCNCoQB/v06RM7hw033NDgakUQjArEuWuvvda+dhA24+L++++3oqMLxNC99tor0RazD3R4ds7aRCfpIBEQAREQgYoj0Lt3b/Piiy+aUaNGBXV4K26RWpAIiIAIiICRSKebQARKkAAiBGJEOPigj2jiukG657t162YuueSSOsf//vvvhsL0OJSSxHvvvVfHuYQAEde4whfHdt1118h6VYhn22yzTS0Ro1OnTgbR64UXXqg1LUQ83HF+INDtvvvuSaZvj0EMQ1hJM+CI2MNcXCCO4ubDGeiLlzggEev88AvvZ5sXTBGPwg6ybOcleX7EiBFBp2AcW1wjTjhlPIQ0nGB+1Hc/GQtmuOTC4d9P7rl//OMf1gHqom/fvubee++1P15wwQXW8RYO7uPddtvNPty8eXMD/3AgQLKHLhDiOnbsaMVK//VCt1WaJSy++OK1hliwYIHtwIzImW0dgwYNMj179gwOIx07TtCO2kd1LE5yd+sYERABERABERABERABESh/AhLpyn8PK3YFpFRSsBzxp9oC5w/ONRcIE3yod8LN7Nmz7Yd+X0zA4YWg4IffJZbHETxw6K2//vqGdDtcQPxxgdjku8BI4UPkc4GzCScWabL8+4knngjEB9I1n3rqqTpbdeGFFwbXYH58A+yEOESv/fffP3CURbmecBH5Yh7dbvfZZx9DuiViB2t0LjouvvPOO1tnU5pB+uxJJ50UDOnXDvvtt98MIgwpkwSCCqmw/O2CvenVq1edKSEk7bTTTvbx0047LXj+qquuqsU9rbUg5F599dV1hkOgQuhdb731rLPMRdgBxuP13U/2ijWTVup4DR482DrLuL/nzZtn04Fdx9OwSHfCCSeY8ePH23Mvv/xy06VLlzrrIeXUOeyiBC5EV85z1+C+g43bM0RAXnMu/v3vf9s5+RF2u2611VZ2jzfddFOz0korWZHdOf6OPPJIwxpd/PDDD/Y51uoLytwPzIF7ijni1CNNFpHafx2mdT9oHBEQAREQAREQAREQAREQgdIiIJGutPZDs/l/AghINTU19idcLG3btq0qNr5IR722qFQ36sH59ctIBz399NMDTqTf4WBzAhb10hDI/PRFRFDcQ04sQRj1A7Ho0ksvtQ8hylFzy3cU4Sbq0KGDdclF1YIjlZE5uHjkkUdqpS4itCGGUG+PCAt9OMr222+/4HyELEQaP6gjhmjnApceKZJpBUIJ7jyXlhm1H9T3Q5xxrM877zxbS9AF6/PFLx5H5PEFaIS+0aNH21MQQvv375/WEoJx6BhMiqgf8EJQQlgiEDmdMzAs0tV3PxnfF/n4GcHNvdbdvBBicfERpFr7adik+0ycONE+xz4z/3AgYuMUdIFo54ef9otASU04X1RlP6nH54REnJGuRqQbxxePu3fvbi6++OJa16DOIDXziPBr0z+Q9zZ331CfsFmzZqnvuwYUgVwJ4HTGpcpr4K677oothZDruJV0PK9bvpzh9yi/J/h9SI1L/qYTMiUgwqUPKmn9/lr4HTd16lT75QK1RuHA++iSSy5pO9XjaM4UdGjnPuP/fnxJwbnw5f8I/B8i/CVJpXLUukRABERABEQAAhLpdB+UJAE/PZD6YtQZq6bwRbpjjz3WnHnmmZHLJ93PCVK4cEhndOF3iOUxUgz54OAHTjxX/yxKZKNW2WWXXWZPQcTgP9uIF6uttlowDIIOjjacUOFUVd+B5s+P/8jTfAEXn++SQ4DzHWW33367/aBD8J98xJRw2iHP+dfBcYS4mFb49c0YM0pU4nFSgp2DL+ycCu9FVN05UjqpeUcgOl555ZVpLSEYx3eh8eABBxxgHWSNGjUKjqGmHh88Ea+4Z/zutfXdTy7ii4C4E2lgEQ4ETtdMIZwCzYc1l6IbFjrdOF999ZV1jboIi3RujTzvu+T4YMmXAjj0/Fp5NHQIN9GA3SuvvGIvgUOU1Ffep1ZYYYXgus8++6y8YC0gAAAgAElEQVR1u+JSjGpewesAYdoFter881O/ATRgagQQEmg2Qr1JUqRdvUwa4NBAB1cqIny4YUhqEyjwQIj5vN8TfEnElxOK2gSoLXriiSfGYqmW/7sg5Gb6PxpfOLlaqHGw/PfkqGM+/vhjNdPRC1AEREAERKBqCEikq5qtLq+FSqT7X7rrcccdZ5suRMWECRPM0UcfbZ+iyP3DDz8cHOYLMtTeoklAOPzaYDjtbrrpplqH+CKe/wQCDseT9kpH0rjumQh8CH0EYszmm29uU2JxMjmXkhuXdEGuzzfvLnzhK85RyLEUUqYRA0EaIyJLWkHqKl0+XcR9WPDTH8Mpt77oGpeOi6BDh1gCFxgdQdMO36HG/YJTLix6IlTx+qPDanhf67ufdLRdd911g2Uh+kU1C/EFsLBI5z+HKArPcODsxNkYt2ekWLu6jghwOF9ISSaNORxh4dg973dg9s9BsMN5yR6ScpuptqDvGGYMuhY3btw47W1PZTzciy1atKg6V3MYHs4e3ndxy2ZqesJ5mRyUqWxKAQfBGep+Z2RqClSfKfAFCO+bvBfxJU+STsr1uV7a52ZrAMOXV23atEn7siU3Hq43fn/HNc+JKhcQXoQvCoefU03OkttyTUgEREAERKDABCTSFRiwhs+PgES6ZCId6SX77ruvhRxOFUU8c+6OuG+ySV/F9UXEdcFELMKxl6l7Jc4vnERhp56fmhh3JyD44RQkrTXcSdT/dn3gwIGRdd0Y1xe4EHFcim5+d1/ts/z6ZKT8OodXeGw/pTUsmDIf5+5DrPTr27lxfEE003XqsyZfnMJ16ZorJB2zvvuJ69IX1eJEKe5p7m23ty1btgym6It0cWsgVQ+R0cX7778fiL+kpYWbYUStnz3knkOIjgo+mCIG+zUdoz5c4vw75ZRTIsW6r7/+2my22WbBaWHHX9J9KfRx/vsxDTeWX375Ql+yJMfn3sE55X8Z4iaK05c0P/99MlNn4ZJcoDcp/wuSJCJLPuvh9TNs2DB7alwTmHzGLeY5CO04d3EjIzL65R2i3OvFnFsxr8UXMIjWcMA9SvkGV7IgrnZoeH6UKaBeJ2PQQdw1F4pr/lPM9elaIiACIiACIlBMAhLpiklb10pMQCLd/0S6TG4MvyFB2KHl17qK+0+y32UyU5ooqV3UyyJFFWdTVLdYxDbSe/zmFb4oFN58HFQ0v6CmWJx7iFRePrwRCB0uHTQ8Fh8GcIkRaae7+s034ppjcF0/NTicOux/4I1zpfChhPp+Lkij89NQE794MhxIAwLXoRY3o1/TMMn49d1P/37L9MELccPdY4iiiJYu/FpwUWnDHDd//nzrznFBrUVXc+7nn3+2jVPiAuES4Zr0rST8+ZDO64IP5DRSCTtEuQ6pt6Q8+3XveNzf81J2i1T7+7G7V/wanTyGAIuDF7eUS2vlvRJRmDplvL6aNm2a5KVVcsf4X5DwJQPieNrhu/Uyvb+nfd1Cjuf/3sWFveqqqxbyciU7NjVYXa1Zvshw9TmTTpgvGPmikcj0ezfpeDpOBERABERABMqJgES6ctqtKpprtX8o9NMj4+p2cTv4Hxrp/urqt/Gc7z6KK7DvfxDDAeA6lGa71XAqkS6Iy8x12uQcCo07UY2fqUODGOQCYYYPewhp4U60Udf003kzNYTw03apHUYKY1rhj82YvuDjX8N3eIXdfH7DBpp7ILyGgzRTPzWqEPXJfHfluHHjbPpxLlHf/cSB5K89Toj069YhgJFm6QIBDQcoQcML57bw1xF20tHFlVphLvwP0jyGoEfzBz5IxqVuJ+WE8MacKYLuUmo5lxqDfoMTHpNIl5Rqwx8XTqGOE4gbfqbpzIDaoHzpQtARmnTUtMP/PVeJIl0h3sPT3oNCjeeX26A0gOtinvR6CN2usRK/F/mCR2FsYw2+AKi2ZmraexEQARGoNgIS6aptx8tkvdUu0l1//fVWgCDofhruDMrjfmdVfsaVgNDgAieQc/VECX2ffvpprWL4iGY48/yg1hv/IeQDml8rzj+GVFoEH4Jrug92/ExTAj7gETiUEAujCqnjPuHaCCR+wf9weiTz8ZtWuHmQQupquG2yySa21lpaQde5rbfeOhgOYdJPUeSJsDuLVB9cgi4GDx4c1PvLVGPQF1YLUc/IF7+imiFkY1bf/SRVkvqILuKacCAYu3pf4T33hcK41GFEOYRgF3QAXnHFFYOfeY5jiPBe+QzmzZtnayhS387fG+5XGkzgAPU79PrnkhrJvezSH6NSzsMNLuhmXF+RMNse5vN8tb8fw8wvDVAI0YBad0mcm/nsXz7n8HuH9zqCruC77LJLPsNkPMdvqBP3Ws7lojAkDT1THchs4/HaZpyoBkXZzuV5/33ivffeq9dcklwv7hjWwO9/Skg0hJuTWrl8yUbQAMr/HZpkXX53bN5HaaykMKZjx472/2SFcreKsQiIgAiIQGkQkEhXGvugWYQIVPuHwnATAlw4fqoctY9wZLkPUTxHOupyyy0XkKQrLEICgYONlFAntP3444+242Q4bZUUE1cXzm+YgDuNIv3hwt6kTpICyXgEjjHqlrnwu98xR5xFfrdQjqMGDe4q17GTAvV0RnThd/qkODV1yPx1hjunpp02yIcdXHwuTTRKZCPN0Rflwi41v+FC2G3o3/q+OJVPzbhsbySIuLy2CFyYvpCV7Vyer+9+cp/4DgD2lgL84fAFZubL/euC+liIBgQNGth/F4hquHMQuf0Ii3S+szHOQUqDEFx6fNAllZvXl/vgTkF9RHECxxGukXAgFOMOchGVXsy9tcEGG8S+fpLsSTGOqfb3YxjzZQMiNcEXGrxP1adzK85ZnMt0iOX+5D4jTZ73BxrVxDVR4HcDr0OOId2WWmC8j3N/ImyQGohjNkkqOzUh2VvelxG3qNVIh26E5yFDhgQuaIr60wQlrWDOfPlBOqTrYs1rBTc4rzH+JBUsSW0fPXq05QgD3mNIj+fLGsZcZ511sk6b33s4XxHJnfsVdy3vQ4yRSw1GX6RriI6kjzzyiP2ijN/f7vcyPLh3M3VgdZC4D2ABT+4Pfu9xv3MuX/KEu1zHwfUdzzTkiavtGXe+/0VL+Mu/rBtawQe4+4svbhHSFSIgAiIgApVJQCJdZe5r2a+q2j8U+iIdm4lIgKi2+uqrmzlz5pjHH388EI14nppnriab23y/mQKPkWqHoECKHQXxnejk3yx+J00+hPqC29lnn23osErgwuODQLho/iuvvFLrW3tcCXyD7hx9zIG5knqI+4x18OHB75LIY61btw6m5ae98CCCDR8i+eDEhzKuGY60HUl+LTWuhTORuml8+OHDECKj+0AU1ZmVD5E4tggchQhwUeELklF7Wt8XNvOmoyqRTzH4NPaTD+VDhw4NlsJ9hRiG+wX3GR/O+NnxDN9T4ZRZPjjyumDPo2olcqGwSOfXO+J55kBnXZxxON8QWZ2T1b3+mIcTTnyhkOedAMf8+XBLepffXCDKpeoAILQ4gRqBGXEdAWallVayrzPEdf4mNX2FFVao7y2Q1/nV/n7s9hgXpwtECJrlhOsMJgHMvcqH7LjusAhEiM+87/tBejjCtAvEOmriudeKf2ymdFxex4j0Sbtg816fROBJsvawAzzTObDFtXjnnXeaJZZYos6hOK1xbLkGSVFj8fuF351x4ZdUiDqG3zf8nkP0SxK+SFeIuqJxcyANkt8x7ou7qOOor4oTKy54r+G9MFPXYhqnUBs23OQpPKb/vhblPs/GktcIzaSIXEpxZBu33J+XSFfuO6j5i4AIiEAyAhLpknHSUQ1AgA8qfEuOG6za6m/4ok429AhWuDyimi/432ZHjcO34q4DG88jDrr0vXANJp7nQ1PUB0Kei6tb5HdHdXPgw2dUt1hEQVxO4SA1E2ExLnCP+B/UEKJwpaQVv//+u20m4MSUTONGOaZ8YSlT6g4f+nEdEHwQ8p1YaawF4cm5zPL9Jr6++4lzEmEt3GCBPaS7X/j+wtmyyiqrBMtHYCBlNkpkdgchnvofNMMiHcf5rN15cfd3uKaj36gk27nc64gMvjvU38twam7cPuM4RMRtiJBIZwx1DnGo+e9b3C84hLh3+WIBIQfnViYBI5zyzf2BcML7ly8yI+zyu89Pu/T3Idt9wNwQOqJSP8O1JbONlY/IEjdmuKNxtmvzPE7lddddt9ah4UY7cMTxjEuP0gn+PuEuw7EajrBAB3NEUN6bfJGdsakzmS2Nlvcm37lXrG7NXJemQIiW/vsRzFxaP4+zDu6hKMHTb0KVbU/OOOMMg6M8U/gNfvJpUsSXIq5ZyY477hiUi8g2t0p/XiJdpe+w1icCIiACfxGQSKc7oaQJ8O1wLqkmJb2YHCbHhzWcWgTOGkQGl6boD0PKK8/HpV0heJAS4WrD+OfiUKDOyxFHHBG40cLpqn5n07jpI4jgLMqUBkNaU1RdPX9MGk6Q6hUXU6dOtY0owt/yI/iQTorowjr5cEpH0LALJQf8kYfy4Y8PJ67+XvggOAwbNqxWTT13jO/cImUX0SYq+DDpPvxcdNFF1iWTZvj7QIomzsp8or77SS027rs455s/p3DTB57jQzSuzvD57DlOEF47pPs5wQ83ZrimIh9suedc6mwUB+4l6imFXTSkqfK6ct0L4xgiyOIaJIUwUyAqc2/FCeDMA9GAdMSGCIl0f1GnPmKvXr1i94ljuAdxb0UVykfs79KlSyCccJ9yrHPjhQXwsNs1TkjBneuu57+mo1LacR/7zjKcYjQc4vcB77HU9gy7k3HsbbTRRqndergEEZRoyuO+XOG1wnsojPjDa4zXKF/Q4QAOC59+0yPWgBDkaq8hBPL+wHqIKJGHsamz567P7xG+wHBuWd53EJriSjlEwcAl6LvAiyXShb/Egg33Kcz4He93RY+qL4irHQHa/+KEew8nG++bsPCdn0m+QPI7gfPe5XfbTnIjvfDCC5Y/wReHfIGo+F/Nw3y/ZBNDERABERCB8iAgka489kmzrEICOIWoPceHI+rz4AwgfQYHAR/W119//di6RT4uPvCQukr6K6mZzZo1s+kjpKPgDPD/MxxV4Jk6RzgZ+ODmxC+uzx8cTYyVLfWF+fBhiA9lfHCi8DEpr/zB4cAHzDXWWCPRLrN+xBlS/3DLOfGFD11cg/UVStjlgyNOGEQLPrjgcsE54epAhevt+QtC8ORDG6mMcZ1tWQMfuHCQUuMu7XXwYYw0OD54IpLxoTjfqO9+UpML0YF7gvuSIMWT+8o1AeEx7r9ll122zjRhhcuObrvsOa8TvwssbjfSlPnwiYgRF9zXjIMQjlsKkYV5IBpwbqYUU5oJ8PpBvOGehCdOB1xz7LPfrTcb52+//damqrFeXh/cS4gO3OO4ZNIWnbPNx39eIt3/aPD+w2uZe8t3LoV58vqirpsfCEkuZZb95P3UT5elHhhfdjixJDxGlDjuu5+5FimPOLEJrkXDEj/8lHrmwDpWXXXV4BB+XyBA+125C9HExs3PXSeXDrK8Pvy0zTAD975Bt2YX4VqnCOOIfy6iSiT4jnb2idd4pjqE4QZCxRDpECSpF+jExDPPPNN+ceeCe4rGN+75qDIHpD3zBZOLKOek3+033KQq6r3EF+ninIyZ3oP8ruqZSkTk8j5WCcfKSVcJu6g1iIAIiEB2AhLpsjPSESJQ8QT4cMGHsygxpOIXrwWWFAHcszU1NcGcolxwJTXhKpgMoghCIaIxoqTiLwJ8iYIQg8hLE4iwszP8pYfv/vLFEgRrUlsRS3yncLgDc7hJTlTdOd85RQ1Q15jB7RnONCfYxNVrC7vMENPjvlioz73gC4bUcYxyH0aNH25gg8AelcLpd7PGJcc97MJvHsNxNEYKR7jkQ7Zap+yjL8wXQ6Tz69fyZRFiZLgzrSu3wB7SBMRvxEMdTVxu7p6gti31UMNBKQrGJpJ0Bt93330DJ2M+Ip1fU1ci3f92QyJdfd5xdK4IiIAIlA8BiXTls1eaqQiIgAhUPAEao2y++ebBOhuiQ2LFQ9YCUyeA2DF+/Pha7qxw/UnfXYTQQXokApirQ+lPKiodHVGONHgiTljyxY1wE5uw6ISrGddoVFAPzKW9PvXUU9YtnHaQ7uuETUoAUAogSfiddsMdnv3z/Zqs1DQlBdSFXzMtrsYazmk/VZ399b9ACM813L26GCLdgAEDAucxNUz91FZ/fjjqwin/PB9uzBRu3OTG8O/dJDXm6Bzu6uHlI9L5dT8l0v1vJyXSJXmH0DEiIAIiUP4EJNKV/x5qBSIgAiJQMQRwEpFC7aIYH3QrBp4W0uAEwp25XYdPRLwkNQVxNSEo0ZAiHJdeeqntykogzvjpmu5Yv54p6dek1LoIN1vI9NrynVB+1+80AZNO7mrC3X///Yk7qPpNX+jKfO6550ZOy0/RJAWUVFAXpIC65hKZUm3pauvSj2+66SZb3y4uKFPg114rxnuXL3TSNTxTan/UvHFw+umxpHBHuRL961D7lXIbmcI/vr4inWrS/Y+0RLo034E0lgiIgAiULgGJdKW7N5qZCIiACFQdAWoxurQ0amZNmTKl6hhoweVLAFEOd5cLaliSJhyuVxZeIeIKzi9EIWqQRgVpiC4tk2YPxxxzTJ3DwkKcEwk5MNx99L333ovtWOo7oQqV7ooY79J7c6l7hzhJTTkCZoMHD47k5bsBTzzxRNtcyIWf9htOhXXHhPeMVFHqv8UFnav9LrKFFunCwi+CbK51RseMGRM0ECINNqpBFev1BdUk94N//+TTeMR30sW5Rsv3XSL/mfO7kd+R+Qiy+V9VZ4qACIiACBSbgES6YhPX9URABERABGIJUPeJroIEKXak2ilEoFwIkCKKOESERWZfGOJ5XFfdu3c3NDho0qRJ1iX6ddTo7H388cfXOSdcF+2tt96q1fzEr9OWSRjz0xtzcbllXYR3gO9SowkLTXiSBB2TXa09Oi8zv3CEBTZciG5fONZ3CkY12OAYv2EKP2dzFBa7Jt3s2bMNKc0ustXMi2IbrmkX9X77xRdf1EpFpu4hqdyZwuebz/3jp23TTIX0cMVfBKgR6jdJEhcREAEREIHKIyCRrvL2tGJWRAF5/ug/IxWzpVqICGQl4DsowjW1sp6sA0SgQATouvvVV1/Z7quZwm8OEW7c4LuL6MJKB+eomDdvnhWnScl06W0ch2OMlEviuOOOM9RSiwr/nLAQ57vQ6PBNA4twUAfST+vM5iDLF7nvzorq0Bo3brjLbVTdyrDARvMEPxXVT4WNq2t3xRVXmMsuuyyYxqeffpqxuyt13+js7KLQTjpqGrZu3Tq4Hq44hM+o4H0VV2WXLl1qibZhls756Y/hs+LxJC4uX+SN6hab7Z6ZPHmyOfjgg+1hmeoOZhtHz4uACIiACIhAORKQSFeOu1Ylc6ZAMyIdNVNwIChEQAQqn4Dv2qBI/oEHHlj5i9YKS5qAL/ggbCGwLbbYYnXmHK5HF+6e6jvhSPWkI2w4EJwOOeQQWwcNJ97LL78cdOtEMEI4IhAwLrjggkhufhppWFChEy0Ciovw8wiRNFWgNpmLCy+80D6WdlALjd/vBKKgEyCzXSfcXCaq2+j5559vSGN1Ee4STYOEo446yj69zDLLWFG0adOmwfGkBuPodc0PaGpBc4tMEU4nLkbTG1/oRBTm/ginS+NSJC2YCKeO+uUFeD6816QVh2sfhptwRDHBIepSZ2mMElVjMRNL7vtu3brZQxAeESAVIiACIiACIlAtBCTSVctOl9k6/Q9Fmb4dLrNlaboiIAIJCPDhlk6JG220UYKjdYgIFJbAiy++WEssRugg1ZT6YwsXLrRCDg0d/HpeFLtHJFpkkUWCydEkAVHFxdlnn21ofNC4cWPbxGDcuHEGcckFIh3ps04QHD16tBUIiUwdLw899NCgYQR17A4//PBagHw3HU+wHr4UQ6DDWcVrz49Mdd/qQ/7aa6+1opALWCDutGnTxoqUuKkQFZl/uKuq7yrkfNJZO3ToYGvs0YUVIclF3759TZ8+fWpNlXpu7JETI0mth227du3sl4M0k/C77oa7z5JyiCjL3wT7vPjiixscey569+5tll56afs4f+iki5DGfqcVYWEYMRWGOOxwziF2DRkyJLgcKb+wckEHW9x1dPp1gejJ+TjgEJrD4Y+Be3D48OGG92ycfVEcaCJBKrPjABNqqzlRlHuc/+fhIP0/9s4E3Mpp/+MriUIpSlFJhpCOKUPJrFIKlZIhpJSZUrj3GhrMlLquWZnClTJnaHANKddQMmXMVEmGokIi/s9n+a9913nPu8+e99nv3t/f8/TonP2utX7rs9bZ2t/zG7Dq1asbflnjOv/yc8Ava2howc8C/6UJS4cOHbKFUfOIgAiIgAiIQEERkEhXUMchZxwBiXS6CyIgAiJQOASmTZtmSw+UYlQzEVIIHwhGydh2221n66RttNFGFR73O5O6F4nkCgpjvHbrrbeazp07x+ZAAHJ16KgJRm2wMPPXOO+888y5555b7jFqmSF8EUUVzxCtXOfVVKLckuHjnvnxxx+t2Oi6p8Yb27VrVysE+cYeELwSjUXgoaECjIM2e/bspCIEwxoXjB071owZMyaV7dpnqaWH39kyhDHSQRNxcOs999xzZtttty23PAIdNeQqM9K8SZnFuN80j8CSZRic248E9VNjU+HC2o0bN05liJ4VAREQAREQgUgQkEgXiWMqPScl0pXemWvHIiAChUlg/vz5MbEorGZVYXqdXa8QlEhXdV1Fw2ZHCCJqi0g2IrrCDMGPNNVx48bFdZB57r//fkNTBN/8SLzK0i+ffvppW7MOi5cyjriDH8EUUzp80pQCIQdxDCMKjX3lwhAKER6dIBi2RlCsdM+Q9kqUn4u4Co5FvCJSb4sttojrOs0WiOALE0kZRErs0KFDK5zn1KlTzcCBA1NGwrnuu+++KY+rbADRfDB0qblhzyK6Eh3od5/1n/NrgQbHI0g2atSoXDSpq7dHN2FEzHj84vntRzdefvnlNioxFeNnhEjLevXqpTJMz4qACIiACIhAJAhIpIvEMZWekxLpSu/MtWMREIHCJKD34/+dC6IS6ZSk93399ddms802s80CSOcjlXXjjTdO6hBJ8SMyb968eQYBkIgv0iGJkKtsngceeMAgkPTs2dNGNIUZQiApiytXrrTNKerUqRPXJ8Q6RFj2Qkqp36iJ9FfmQODJpZEyjPhJRBfppy41FEEJFn5zhKAfpFvCkZRkxsKRs2AMtfmC9dnC9rF8+XKbqkxkFmnHCJWkUyKSxhO1mGfZsmWWDymj/CGFNviH769du9Z+nznr1q2bE5Rr1qyxqbaIjvDgDhBlRhMRIiERBsPqKPrOcK+oEUgXW5iQdty3b1+bAsw+iH6DUbBGHF1tuSuOg2Ph9s0a7u9woJNxsCEYkYDcRYxnfG4+W+YhpXaHHXawaa8yERABERABEShGAhLpivFUi2BP+lBYBIeoLYiACBQFAb0fF8UxahMikDEBREyi1/xaixlPqgmSJkC9RCInS7HsQNKQ9KAIiIAIFAEBiXRFcIjFuAV9KCzGU9WeREAEokhA78dRPDX5LAIiUGwE2rVrZ0U6mn/QwEMmAiIgAiJQnAQk0hXnuUZ+V/pQGPkj1AZEQASKhIDej4vkILUNERCBSBMgfRnLZZ3ISAOS8yIgAiJQJAQk0hXJQRbbNvShsNhOVPsRARGIKgG9H0f15OS3CIhAMRGQSFdMp6m9iIAIiEB8AhLpdDsKlkCrVq1sUWYKGav+RsEekxwTAREocgIS6Yr8gLU9ERCBSBCQSBeJY5KTIiACIpAxAYl0GSPUBLkkQJHcyjrT5XJtzS0CIiACImBs58vevXtbFBMnTrTdHWUiIAIiIAL5JSCRLr+8tZoIiIAIVBUBiXRVRV7rioAIiIAIiEAECPginSKbI3BgclEERCDvBHifrF+/vtl2221ztrZEupyh1cQiIAIiUFAEJNIV1HHIGREQAREQAREoLAJ0Ezz66KNtVPOzzz5bWM7JGxEQARGoYgL+LzJ22WUX06NHD3PkkUeaevXqZdUziXRZxanJREAERKBgCUikK9ijkWMiIAIiIAIiIAIiIAIiIAKFTOCLL74wV155ZYVfYrRv394cddRR5tBDDzXVq1fPeAsS6TJGqAlEQAREIBIEJNJF4pjkpAiIgAiIgAiIgAiIgAiIQKES+PDDD820adPM9OnTzVtvvRVzs2bNmja67ogjjjBt27ZN232JdGmj00AREAERiBQBiXSROi45KwIiIAIiIAIiIAIiIAIiUMgEZs+ebcU6RDtKBjjbcsstrWDXsWNHs9NOO6W0BRr4kFqrBj4pYdPDIiACIhA5AhLpIndkclgEREAEREAEREAEREAERCAKBKZMmRKLsPv5559jLrdu3docfvjhhrTYpk2bRmEr8lEEREAERCAPBCTS5QGylkiPAL8t5LePPXv2TG8CjRIBERABERABERABERCBAiCwYsUK89hjj1nBbubMmeU86ty5s+nQoYMV7DbeeOMC8FYuiIAIiIAIVBUBiXRVRV7rVkqAf8iUlZXZZxTWr8siAiIgAiIgAiIgAiJQLAS+/PJL8+ijj9pmE/Pnz49tq3bt2qZLly5WrONPtWrVimXL2ocIiIAIiECSBCTSJQlKj+WXgN/OXiJdftlrNREQAREQAREQAREQgfwQoMkEEXZPP/20+frrr2OLbr311jGxbu+9986PM1pFBERABESgyglIpKvyI5ADYQQk0uleiIAIiEDhEBg5cqRp0qSJ2Wqrrcxtt91WOI7JExEQAREoIgI//PCD+e6778z3339v/vzzz9jOatSoYcaPH28OOOCAItqttiICIiACIhBGQCKd7kVBEpBIV5DHIqdEQARKkID/fnzRRReZK664ogQpaMsiINaUwLMAACAASURBVAIiULUEBgwYYC6++OKqdUKri4AIiIAI5JyARLqcI9YC6RCQSJcONY0RAREQgewT8N+P77nnHlOzZs3sL6IZRUAERKCECfz000+2mcTLL79sPv744xiJ6tWrm912281st9125uqrry5hQtq6CIiACJQOAYl0pXPWkdqpRLpIHZecFQERKGICej8u4sPV1kRABKqUwOOPP26eeOIJM2PGjHJ+7LfffrF6dJQawKZOnWref/99069fP1OnTp0q9VuLi4AIiIAI5I6ARLrcsdXMGRDQh8IM4GmoCIiACGSRgN6PswhTU4mACJQ8gZdeesk8+eSTZvr06Wb58uUxHjvttJPp1KmTFedatmxZgVNZWZlZsWKFufTSS03//v1LnqMAiIAIiECxEpBIV6wnG/F96UNhxA9Q7ouACBQNAb0fF81RaiMiIAJVRODtt9+23VunTZtmFixYEPOiQYMGplu3blaYa9OmTaXeNWvWzL4+aNAgM3jw4CraiZYVAREQARHINQGJdLkmrPnTIjB//nzTuXNnO3bixIkJ/+GS1iIaJAIiIAIikJCARLqEiPSACIiACFQgsHDhQvPMM8/YiLnXXnut3Os9evSw/85FnFtnnXWSoieRLilMekgEREAEIk9AIl3kj7B4N0AXK/6BM27cOOPqcRTvbrUzERABEShMAhLpCvNc5JUIiEDhEVi1apWtHUfEHOLc2rVrY07uu+++pnv37laYq1u3bsrOS6RLGZkGiIAIiEAkCUiki+SxyWkREAEREAERyA8BiXT54axVREAEokvg+eeft6Ic4ty3334b20iLFi0MUXNdunQxW265ZUYblEiXET4NFgEREIHIEJBIF5mjkqMiIAIiIAIikH8Cvkg3a9YsRTbn/wi0ogiIQAET8N8jcZMouaOOOsqKc61atcqa5xLpsoZSE4mACIhAQROQSFfQxyPnREAEREAERKBqCdBNcMiQIVacGzZsWNU6o9VFQAREoMAIfPTRR+aSSy4xNIFAmDv44INz4qFEupxg1aQiIAIiUHAEJNIV3JHIIREQAREQAREQAREQAREQARH4HwGJdLoNIiACIlAaBCTSlcY5a5ciIAIiIAIiIAIiIAIiIAIRJSCRLqIHJ7dFQAREIEUCEulSBKbHRUAEREAEREAEREAEREAERCCfBEaMGGE7x44bN860bNkyn0trLREQAREQgTwSkEiXR9haSgREQAREQAREQAREQAREQAREQAREQAREQATCCEik070oWAJ0y1q0aJHp2bNnwfoox0RABERABERABERABERABERABERABEQgGwQk0mWDoubIOgG6CZaVldl5J06caNq0aZP1NTShCIiACIiACIiACIiACIiACIiACIiACBQKAYl0hXIS8qMcAaLoevfuLZFO90IEREAEREAEREAEREAEREAEREAERKAkCEikK4ljjt4mJdJF78zksQiIQPESuPPOO02dOnVUfqB4j1g7EwEREAEREAEREAERKAACEukK4BDkQkUCEul0K0RABESgMAj478fvvPOOFetkIiACIiACIiACIiACIiAC2ScgkS77TDVjFghIpMsCRE0hAiIgAlkgoPfjLEDUFCIgAiIgAiIgAiIgAiKQBAGJdElA0iP5J6APhflnrhVFQAREIIyA3o91L0RABESg6gnwXjx//nxbdkARzVV/HvJABERABHJFQCJdrshq3owI6ENhRvg0WAREQASyRkDvx1lDqYlEQAREIG0CZWVlZsWKFWbUqFGmV69eac+jgSIgAiIgAoVNQCJdYZ9PyXqnD4Ule/TauAiIQIER0PtxgR2I3BEBEShJAs2aNbP7HjRokBk8eHBJMtCmRUAERKAUCEikK4VTjuAeCefv3Lmz9XzixImmTZs2EdyFXBYBERCB6BOQSBf9M9QOREAEok9AIl30z1A7EAEREIFkCEikS4aSnqkSAgMGDDALFy4048aNM02aNKkSH7SoCIiACJQ6AYl0pX4DtH8REIFCICCRrhBOQT6IgAiIQO4JSKTLPWOtIAIiIAIiIAKRJSCRLrJHJ8dFQASKiIBEuiI6TG1FBERABCohIJFO10MEREAEREAERCAuAV+kmzVrliKbdVdEQAREoAoISKSrAuhaUgREQASqgIBEuiqAriVFQAREQAREICoE6CY4ZMgQK84NGzYsKm7LTxEQAREoKgIS6YrqOLUZERABEYhLQCKdLocIiIAIiIAIiIAIiIAIiIAIFCABflEycuRIM2nSJOtdgwYNzI033qimagV4VnJJBERABLJBQCJdNihqDhEQAREQAREQAREQAREQARHIIgHKDdBIDaGu5oa1Tc2N6pgfli62KxDZ3K9fvyyupqlEQAREQAQKgYBEukI4BfkgAiIgAiIgAiIgAiIgAiIgAv9PgMi5oUOH2q9a7tPR9Bo62op0MyaMMc9NGGu/36tXLzNq1CgxEwEREAERKCICEumK6DC1FREQAREQAREQAREQAREQgWgT8AW6rqddatr16F9uQ5++9V8zYfgpZvVPKyXURfuo5b0IiIAIVCAgkU6XomAJTJ061SxevFih/AV7QnJMBERABERABERABEQgmwSoPzd+/Hg7Zc+ho0zrjr1Cp1+yYL65fejRVqhr2bKleeaZZ7LphuYSAREQARGoIgIS6aoIvJatnAC1N8rKyuxDEydOVHFcXRgREAEREAEREAEREIGiJkB6q2sQUZlA5yD4Qp1SX4v6amhzIiACJURAIl0JHXaUtkqh3N69e0uki9KhyVcREAEREAEREAEREIG0CKQq0EmoSwuzBomACIhAwROQSFfwR1SaDkqkK81z165FQAQKk8Cdd95pHVMnwcI8H3klAiIQbQLpCnS+UHfD6Z3tlzSSIKpOJgIiIAIiEE0CEumieW5F77VEuqI/Ym1QBEQgIgT89+NZs2aZJk2aRMRzuSkCIiAChU8gU4HO7XDOtElm8qi/usFKqCv8c5eHIiACIhCPgEQ63Y2CJCCRriCPRU6JgAiUIAG9H5fgoWvLIiACeSGQLYHOOTvrkfFmyq0jTZ06dWxNZxpKyERABERABKJFQCJdtM6rZLzVh8KSOWptVAREoMAJ6P24wA9I7omACESSQLYFOgdh0nVDzNzpkyXURfJWyGkREIEoEFi4cKF58MEHDc0uf//9d7N69Wrz008/mT///NPst99+5sQTT8xoGxLpMsKnwbkioA+FuSKreUVABEQgNQJ6P06Nl54WAREQgUQEciXQBYU6yhM888wzVrCrCvvxxx/NW2+9ZT7//HOzYMECs2jRIrP++uubTTbZxJZO2HPPPU3r1q2rwjWtKQIiIAJpE7jooovMfffdF3c873frrrtu2vNLpEsbnQbmkoA+FOaSruYWAREQgeQJ6P04eVZ6UgREQAQSEci1QMf6q1etMLcPPdos+fR9m/JK6ms+hbpffvnFTJgwwYwdO9ZGl1Rm99xzjznwwAMTYdPrIlAUBN58803z+OOPm0MPPdS0bdu2KPaUzia+/vprc8cdd5hWrVqZww8/PCNBK531Mx3D+9vFF18cOs2GG25o5s+fn9ESEukywqfBuSLAxe7c+a8uVfzDok2bNrlaSvOKgAiIgAhUQkAina6HCIiACGSHQD4EOuepL9Tx72j+PZ0PW758uTniiCPMl19+WWG5Lbfc0nz//fflhLvLL7/cnHDCCflwTWuIQJUTOOqoo8wbb7xh/ZgxY4bZbrvtqtynqnAAAX/MmDF26auuusocd9xxVeFGRmsuXbrUrFq1ylSrVs189dVX5vjjj7fzbb755oZ/O2diEukyoaexOSXQu3dvQ773Qw89pG6COSWtyUVABEQgPgGJdLodIiACIpA5gXwKdM7bJQvm24i61T+tNL169bJdX3Np1Gbq16+fefHFF+0yRJScddZZplu3bmaLLbaILU103fvvv2++++47c/DBB5v11lsvl25pbhEoGAII2KSAY/fff7/Zd999C8a3fDpy7bXXmptuuskuee6555rzzjsvn8tnfa1PP/3UHHTQQXberbfe2jz//PMZrSGRLiN8GiwCIiACIiACxU1AIl1xn692JwIikHsCVSHQuV35Qt2gQYPM4MGDc7bhadOmmQEDBtj5Eegee+wx06JFi5ytp4lFIGoE+vTpY2bOnFnyIt3NN99srrnmmqIR6T788EPTsWNHu58dd9zRPPvssxldTYl0GeHTYBEQAREQAREobgK+SEcBcuobyURABERABJIjUJUCnfNw/uypZsLwgfZLoumIqsuFkbZ266232qkR6+LVbEp3bTonkloWZSuGPcC/EPaRqQ9EfpK1temmm+atZuPAgQPN1KlT7RUmW2zvvffO+DpnyiFjB9KY4N577zWXXHKJHcl75Nlnn53GLP8bAgM6rNaqVSvteRhPVO8666yT8hzvvfeeOeyww+y4PfbYwzz88MMpz+EPkEiXET4NFgEREAEREIHiJkA3vlNOOcU0bdrUFvmViYAIiIAIJEdg0qRJ9gMo1nPoKNO6Y27EsWS8mTNtkpk86i9fciXUHXvssWb27Nl2jb59+5oRI0Yk41rcZxYvXmw7KPIBmDpepMnSZAIBsLI0wZdfftmm0jVr1szWu3LCHg0t5syZY+vlffvtt+bXX3+14kDwg/2rr75qeHb//fdP+IEdoQWBgDI98Qzfn3jiCfP2228bGgcgCpHme8YZZ9jUuHhGUw3GkS7s1+2jrh9zUhOLPw0bNjQnnnhiRqwTDWaPNDyA7bx588zHH39sfe/SpYv9N0LdunUrTMEYUp9hSZRR9erVQ5fhOaIuqevFXHQADrN0fAjOgzDHv2WoB+dqw/HMfvvtZ+8K/9YJGl2K2TvnhhATTyj+z3/+Y+9W165dTf369ctNs2LFCpvefemll8Yi6TjfvfbaywpDqXYCTfdO+U4tW7bMvPDCC7Z+GrUk+fqbb76xdSNvuOEG0759+0TXIuXXf/vtNyuMPvroo3YNjHTXU0891dSoUcP+SVaIX7lypbn77rvN3LlzDT+zvD9Q93K33Xazc26zzTYJ/eM+8wtoxnOnMc6kU6dO9j0s3p0NTkwKM6nMWDZqgEqkS3h0ekAEREAEREAEREAEREAEREAEkidQSAKd89oX6m6//XbbYTKb9ve//9088MADsSkRAymUn2pkCmIM/M4///y47iGKXXnllaHiBh+SlyxZYseSdlavXj1z3XXXmcmTJ1eY77LLLisncD355JO2jh52wQUXmDPPPDOuD+yVPWN33XWXFd58Q5waPXp0pb/gojZXmMCHYOW6f5I6jFCJOMbzTgj112KfpNnlwvDlb3/7W6zWYHAN/Pv3v/9tdtlll3IvPffcc7ZGIUZ0EdFTPBs0OLvGJsHzcM+m64O/FnXDSPl2NeGCfiDCIdggevrGPbvtttvst+jqiXgbNLqVuqg4hEvSOZ0hztLBNBmDD2K3izILjsnkTrm5PvnkEzN8+PCYWBjmF2I4ImI2DVGcO40ImMjgwH3mXoXVrERQIyqRM41n/MwfffTRoS+vXbvWioQ0sIhnvI/wTPA+hD2P+N+jRw/7EoIvv1zIxCTSZUJPY0VABERABERABERABERABETAI+CXCajqCLrgwcyYMMY8N2GsTe9DGMlmCQP/g6pbl06HrVu3thEurVq1slEufhOJsItDdMywYcNiL/FhnS6Yr7/+ekx840Wiy+gO6xsC31ZbbRX71umnn25uueWWuPeTD9auyyQPXX311bHnEW1ee+21uFFOFIp3IsE///lPG/HmGxF/1OlzhvCB4DBr1qxyHW5vvPHGCiIOEXf+fIiFrtB+2GYqEyQy+eEkOgnRwRdWOnfubIguC4qFRM357F955RVzzDHHlNv/+PHjy/Hk65EjR8aeGTdunOnQoUM5lzPxwU1EhBv78I07SdSei6DitaDAxveo4/jII4/YofE6kX7wwQcx0TvY3RMBlUixZA2Bav78+aGPZ3KnmJD3JoRTmAaNdf3vc7eTjSRLZm9EEvJekIoh9G677bblhvgCNi/wc8qdJEqPCEn/rj799NNmp512qrAkYjB3zRl3Y4cddrBiuH+viQBNJouE9wlXRgCxHtE+E5NIlwk9jRUBERABERABERABERABERCB/ydAiYBOnTublStWmK6nXWra9ehfcGwmXTfEzJ0+2Qp0CHUIdtkyPtAGhbPg3ERcEWGG8BY00jdJN3NGpBoRM0Tj/fHHH+Yf//iHja5xFowgQ2SIJzzy4Zk/iGRETGEHHHCAjfByxof8/v3/d2bxIqeCItpLL71k02udkfp48sknx772O3kicB133HHm3Xffta8jMiAM1KxZM/Y88/kprj4nIq2I8oEh4hMGp9NOOy1bxxibxxctOS+EDSfE0aGXSEkn7AQFLgRT0ldh6oyvXZSYL2zwOoLp9ddfXyHdMRMf3Lp+LTjEKCLdEE0xv24kX5M+yZk4QyCdMmWK/ZLIq+7du1fg/MUXX8Qi7IIi26pVq2wk3g8//FDurhHJyrOk4BLZxf3mnpNq6VIn/YUyvVOIWL7gxdrsjZ8Jzpb00V133TW2JKJ7MG030wvGzxqiKGmmTuAmyhLBFAb84d7AhJ9j0tGDQuFFF10Ui1RDECUV2UW7IQRyx/j5xMIEM96j27VrF9tK8GfHj4LmIeb3uYQx4OeXn0ssWWGvMpYS6TK9aRovAiIgAiIgAiIgAiIgAiIgAsZYQYnC8Lt36Gl6nT+6YJncPrS3+eztv6Jq/Ki1bDjMB2RSSxHCKktt+9e//lVBjPBTZhExSMv17fPPP7fCmjMaVRBF48xPO3TfQ4xA0HLP+V1og2l9iAOIhM7vYKSdmxOhyYl7PM8He2eIDKREOgEtLIUTcZQ0T2fUGGvQoEHsaz/t1n0TIQVmLq3VjwZCvEwlWiuZcw5GnwWjktgnUWbUF8OoUff888+Xm5r0TOrlIcg5I3IR7tQ8c5wRbqnv5wuVPJ8NH4KCJ1FxfkQXacRHHnlkzL+g8OtHrwXvmxsUFJcR7cIM4cmJmtRBa9SoUTJHYYWrTO9UUBSlyyzimG8IvU7ARkSuXbt2Uv6l+tA555xjxS8sLJI03nxBgY1fCriuqm6M38SB7/Hzvv3228em9EW+eJ1Y/TOnxmBlUaxMjOh4/PHH2zXC3rdS5SORLlViej5vBPgHDgVjXS2DvC2shURABERABERABERABEQgRQKkqCEE1W3Y2Jx7y7Om5kbZi1BL0ZWEjy9fushce8Jf0STvvPNOVqPp/MWJIqIGFpEmRGH5oh3iGUKBH7VE2pkTt3yxBBEEIYy0Tt+CUU8fffRRhXTJoOjif9BHoAx+1uADObXfnHGufi01hCdEHie2BMVG6uER6YYxjppkrjEA0WeIe37tPgQqGkT4RuQdwpszBDrEMF80YYzrivnUU0/ZdOJsmj+/LzwQ7UQ0ImnEfmogUVm+8Oh8oWkCtcHYuzPEEfd1vFpwPJsNH4hoJAoNo/6ff7bOHxo6UIONaEDqkPmNHBAZSeXFwkQhvk8jEiLCnIWJdHDzG4VwLzbeeOOkjiwbd8pPw2dR7g4CVIsWLWJ1I4n2e/DBB83OO+9s9tlnn6R8S+ehPn36xGri3XnnneaQQw5JahpfvOZnC4E1rGYdArBLYyaKkehEZ/57DOfuR866Z9Ah+IULFiY+B531hWCJdEkdpR6KIgHezMvKyqzr/KbJ/Y8uinuRzyIgAiIgAiIgAiIgAsVPwH0Ibr5zGzNw1MSC3zAiHWIdkTPZrE0Xb+M///yzjUghcsYZkVgU88cQv6gL5YwPvjBFZHMiiz932If7YBpqvAYZCESknVLsP9hNMii4BFMciQAiEggLq1vnR9UQMeaaLiAwuBRXtw/GE9nl13LjNYQFGhY4o75bsJYf6ZFEYzEHQku2jdRTau1hpITuueeeNlKO/bvGHG5NBB3qcAUj4dzriKxEqwXH8TqdXalVGGbZ8GH33XePicN+2nFwPRobhHWWpdaYiwSkhl5Y11PEZ9ZxtmDBggq1DP3PtzyHoByvk23Qt2zcKaJEEd+C9egQu0j/5PM20XphaejZvluIoe5ngfT1ZAVB3jucUB9MVfd99IVZX4iDgd/1NRhV6ebwu7XyPSJ4K+s6S5fck046yQ6XSJft26L5CoaAr/RLpCuYY5EjIiACIiACIiACIiACcQjwIZwPm9R2GnDdRLP1Ln9FUxWizXpkvJly60jTuHHj0G6hufTZ/wDtf6ANpqnF84EP+AhfwVQ9nvdrQyE2+PXQUtkTwqFL4/TTWRHGSK9zUTphkXjBxhfx1qWLLI0tNtpoowqPIAy6hhZ+HbdU9pDps8EmBWHzIRCSokxacKImA2HnG6+7rVsrUx/4WfQjDIORl8kw8kW6eKIvgi8CmLMPP/ywgmAZbJwQLyU2zKds3CnmRcTmvPyoxuB63PchQ4bkNEjGb7pSmUgb9I2Oz6RFY2GNY9zzfsdgUnhdF+Zg+nS8lONgWm2iqEdfpFNNumR+qvRMJAlIpIvksclpERCBIiTAh04+LDRp0kTlB4rwfLUlERCB7BJw3SpJdb3w3lkFmfK6ZMF8c/v5vc3qVSuqJGPFL8yOgEKqJuZHC4WdCuIeH8z9SJjgc37jh0y6LAY71bp6bHSbdOmxRCDRcdZPhcUfP/or6B+F7tlHz549y6X5Bp+j+YbrKnnxxRcbxKp8G00hqJUXZqTowoH07mSiwaipdu6558bqkLk5EV0QK+NZpj4grhx++OF2egRFRLpUjYYALq2XhhOIxEELioHBFGme97uSVtbBNcy/bNwpf14EU37eSDfnT5jF22uq/MKej5fWnmhuUnRdajg/R8OHDw8d4gur3C/uGYa47kdCxmuOEUwNDjtPf2FfpGN+/j+QiakmXSb0NDZnBCTS5QytJhYBERCBlAj478fUoEGsk4mACIiACMQn4KJ/Nt+mpRl43cSCEuoQ5q45sZ0V6HLRNCKZe0ENt1GjRtlH+TDt/k7tumBtKj7wEqWF4FarVq2E0yOmEZ2GEdXod4JNODjwgP9B39Uyo+smqXBYPIGJNYn0c4Ygw7hu3brZlNFEEWeMczXSKlsn1f2k+rxf3J+xCIwwYS+ppkT6HVqDfpBSC5swy9QHBOAzzjjDTp1MbbEwH/zIT1KQXYMA/9lgJB13pG7duuWmy0Sky8adinf+pPmSesrPDuu4dFgiVeMJeKnepeDzpNa61GdS2SsT3v2xNIChZiBGijRReEELps3z/sK9xUi5d41X+Dpe+jN3EmEUS0bc9WvSBZvRpMNKIl061DQm5wQk0uUcsRYQAREQgaQI6P04KUx6SAREQARiBPxC+YUk1CHMEUFHJB0fkikpky2j1hN1u+rUqVNpA4M1a9aYww47LJYues0115hjjjnGuoE44NfGo3i7X6PO9/WDDz4w1P0iIoc1nfmdW/0ovXT2GewKijjgatExX7wUOH8cAh3RW/FqtZFuR7H+Dh06xIr3M7ffuRXR0Rf90tlLOmOo/eXqB5KWTGfTddZZp8JUnD0RjPXr1y/XPME96AsefO+8886zTIg+chavvFGmPgQjorg3YWIve3j44Yft/oKpu75QSG0+16zDBxGsYUZDg3r16pVjFax1GC+KK+yssnGnEMFZk5+ZYH1Dt6Yf5cr3iDwLa8yQzn3yx/jprvGacYStQQq6q2HJ62G1/4JnHmyq4guE/Fw5Ud9fzxfok0lf5ZfYxx13nJ2islp5yXKTSJcsKT2XVwL6UJhX3FpMBERABOIS0PuxLocIiIAIpE6g0IQ6X6AjkoS6Tr64lfoOy4/wo+OIQCFNMWi//faboQMo4pszGhH4HS/9NLgLL7wwFgXlz+V3XiSqi7Wd+f/PyjQSiBRNul8Gmz2wlp9CF9ynHzHFa2HF6altByfn+1VXXRX7kM8YBEGihjA6YV5xxRWZHlHK44OdNEl93WCDDcrNQ/deItVc91NE0u233z72DDXcfN+7d+9ua+2RHkojiU8//dQ+i5iJSOZHOfH9TH0I1oELcnaO+pF+wY6fvmAaFGAQWEkLpdGHb2EiHfdpp512ikWqpZLGnOmd8iPIiIik+UfDhg3L+bxs2TKbVu1SnDNJF0902agTR8MaLJV1vvnmGxuN6oyOvESu+Ua0o38ewfqAfio5HXkRiP1uvsEmIIlSslkbsZ0Oxlg2fgEikS7RDdLrVUJAHwqrBLsWFQEREIEKBPR+rEshAiIgAukRoPh4p06drCBRlRF1uRbooBOMlkKMQ0DbdtttzfLly23aHOIMhdudXXLJJYamCL4hHrr6UQg3CCAId6SIEglEB9H77rsvNgQRjY6xzoI1p1Ipzh92yn6tKf91atFtttlmcS8GXWsR5zCEJ3wkpW/t2rW2jh28XJ0zngmmUT7wwAOxYvfUfSOKLd9GdNm+++4bS0tEVBs5cqRN4ySlcPr06bbTpn+mfM91mvXFVHxHEGFfrobdZ599Zuu7ufRK0gqpN+aX1cjUB9b101X5+qKLLrJ1yTbZZBN7pxCs7r333hhePz2Sb/ops3zNWBquEJUWJuDyTJhIx/dPPPHEmKDJ/Uasoj4hvsCD+8Z/8XHjjTcud+SZ3CkEOL+DLneKKEnEKX4+EUOpP4xA5Qyhi/evXNgtt9xiEEadUWuSlHJ+VkiDJTINsZCOqWVlZeVcoA4d7wPOOK+2bdvaCMkpU6bYVHFnfvdo972vv/7adnV2RpTowIED7dp0caXphDtXzghf/KhIIoYR9hBoMd6bFi9eHBvDPSY6mAhE+PLf5s2b22jZZE0iXbKk9FxeCehDYV5xazEREAERiEtA78e6HCIgAiKQPgGEOoQouinWa9jEnDD8DivY5cvyIdCxFyJ9EC+c4JJof34tOv9Zou2IrPGFH17nw3Jwbj4MI+oh6ubv2gAAIABJREFUBDpLpstmIt+CrwebFyAcIFZVZmH19cL2wBx006R7p9+Awm9QgbhFlFlVGEIjQodvcPfFHPcaUVhEh2FEje2///6xcySqETEMMco3uo369ej8br/uuXR9cOM/+uijpAUSau0hWPkpsQiFiMGVdURlf/6djSfSBdNi450p0YdEUPqW6Z3y6ynG+5ly6/Xv39+eZVh6czbuIT+nnLWrSxdvzqAIz3NLly61UZiJxnJP+eVAsLELcyCa01k4kYX9IqGyZiaVzYcoj7ibjEmkS4aSnsk7ATqooPBj8WoU5N0pLSgCIiACJUhAIl0JHrq2LAIikFUCfuorXV9pJpEPoS5fAp2DRRQb9boqEzNIbSWNlQ/o1apVC+WMAEQKJf//iWd0Fx03blxoNJtfcypRV8ZkDjpY44r6YM2aNUs4lGgcIqfCBC03mM6hpFPWqFGj3HwIPkQQYuzVdbRMuGgOHgjWAQtbIphGirC18847W2EVkYQIJz+t2Z/Dj1aMl6Kcjg/+Gpwhd6qys0AcJioLcSdoCEKI7cHIOZ5FyCEicNddd40JycEUS38+zpJaaPEEbXgRvUf0VdAyuVMIojS9qExIZ2268J566qk5uEnlp+R9gjNxKc9hCxJB6jQB/3XSXomQjBfJSFoykXrxau8x14QJE2KictjaiHiksAbfp/x02WQhhUXkVTZWIl2yZPVc3gkQ8rpw4UL7GzJ1E8w7fi0oAiIgApaARDpdBBEQARHInABC3YgRI8zkyZPtZD2HjjKtO/7VcTAXlm+Bzu0BcYb/b1CbjH/Hs2+EF6LdqFVG/Si//lO8vTMP0WREHvFBnBpupJxRR4sUzHbt2lUQttxcrE/XR9L7+DyRDSPSjagcPvwjvCVrpBkiQhFZ5YQbosm22morywIBLp7RaZPmFEQNITxWpSGkvPzyywahh+hQUl75Q401OvI2bdq0gnukg3Lficryox3D9kFaMvtFvPXTMv1n0/HBH0/jBuqgkUb5zjvv2Pp6iDik55LWGUyrDPrJnWQswm+jRo2sCOl/RuWcn332WUNTBPZRmXEviBB87733LE984W5zH/AlTCh082Vyp0j1xEdSNl3jDsRA7iN3m8i1YN3BXN47ImcRLblXiPyI1fx8cK/g6FKnw3xYvXq1PY9XXnnFjoUZKeWMQeCO90sAfy7uHe8XpKBTtw8WiMmkz1Ym8CHa0hUX472JyFFS2d3f+S9/+B7RiDTASaUBh0S6XN46zS0CIiACIiACEScgkS7iByj3RUAECorAkCFDYkJd19OHmXbd+2Xdv6oS6LK+EU0oAiIgAiVIQCJdCR66tiwCIiACIiACyRLwRTp+A92yZf5qKSXro54TAREQgSgRmDRpkhk6dKh1mWg6ouqyZRLoskVS84iACIhA1RCQSFc13LWqCIiACIiACESCgCt6TirLHXfcEQmf5aQIiIAIFDqBoFDX9bRLDfXqMjEJdJnQ01gREAERKAwCEukK4xzkhQiIgAiIgAiIgAiIgAiIQAkRoLYVhclXrlxpG0nQUCJdoU4CXQldHG1VBESgqAlIpCvq49XmREAEREAEREAEREAEREAECpUAQh1dIxcvXmyFul5DR6fc+VUCXaGervwSAREQgdQJSKRLnZlGiIAIiIAIiIAIiIAIiIAIiEBWCNABlYi6999/30bSEVGHYJeMSaBLhpKeEQEREIHoEJBIF52zkqciIAIiIAIiIAIiIAIiIAJFSAChjs6v06ZNs7s755ZnEgp1EuiK8CJoSyIgAiVPQCJdyV+BwgVAR0EKlvfs2bNwnZRnIiACIiACIiACIiACIpAlAgh1kydPtrPR9ZXur2G2ZMF8M2H4ALN86SKz4447moceesjUqZNZ44ksbUHTiIAIiIAIZEBAIl0G8DQ0dwT4bWJZWZldYOLEiaZNmza5W0wzi4AIiIAIiIAIiIAIiECBEEgk1CHQ3X5+b0MknQS6Ajk0uSECIiACWSIgkS5LIDVNdgkQRde7d2+JdNnFqtlEQAREQAREQAREQAQiQGDMmDFm7Nix1tN2Pfqb9n0G2Xp1c6ZNMlNuHWkFuo4dO5rRo0crgi4C5ykXRUAERCBZAhLpkiWl5/JKQCJdXnFrMREQARGolMCdd95pGjdubA499FCREgEREAERyBOBSZMmmeEjRphVK1eaeg2bWJGOKDqsX79+ZtiwYXnyRMuIgAiIgAjki4BEunyR1jopEZBIlxIuPSwCIiACOSPgvx+/8847itjIGWlNLAIiIAIVCVCfmfRX3osxfmFy/fXXqxSMLosIiIAIFCkBiXRFerBR35ZEuqifoPwXAREoFgJ6Py6Wk9Q+REAEokxg/vz5hprNqtMc5VOU7yIgAiKQmIBEusSM9EQVENCHwiqAriVFQAREIISA3o9L61q88cYb5plnnjG//vqrWbNmjVm9erX55ZdfTLVq1czJJ59s2rZtW2VAFixYYKZMmWI+//xz8+WXX5off/zR9OnTx/Tt27fKfMp0YfZw3HHHmSVLlpgHH3zQtGjRIjblwIEDzcsvv2wuvfRSc8wxx2S6VJWM/+OPP8yFF15onnrqKdO/f38bESZLjwDvxQh1PXv2VERzegg1SgREQAQiQUAiXSSOqfSc1IfC0jtz7VgERKAwCej9OPG5vPbaa+aTTz4xDRo0MLVr1zY1a9Y066+/vv1To0YNU716dbPuuuva/66zzjr2z4Ybbmi/V2i23377WQEszIjgoeN6vu3jjz82V199tZkxY0aFpTfddFMzd+7cfLuUtfUmTJhgLr74YjvfJZdcYk455RT796VLl5q99trL/n277bYL3XvWnMjhRJ999pk58MADYysgtBbivc8hgqxNXVZWZiPpEG0RPGUiIAIiIALFSUAiXXGea+R3pQ+FkT9CbUAERKBICOj9uPKD/P77783uu++e8mkjLk2bNs3Ur18/5bG5HHDmmWfaaLUw69Kli7n55ptzuXyFuYkwY104h9k//vEPc+qpp+bVp2wudu2115qbbrrJTunv5YsvvjD777+//f7mm28eq0eWzbXzMdenn35qDjrooNhSiNkI17LUCTRr1swOGjRokBk8eHDqE2iECIiACIhAJAhIpIvEMZWek4Tzd+7c2W6c39qr/kbp3QHtWAREoDAISKSr/Bx++ukns+eeexr+m6o98sgjpnXr1qkOy/nzpJOSpkiK6xNPPGGL1GO9e/c2iEr5st9//9107drVvP/++7El+ffA2WefbVq2bGk22WSTfLmSs3VGjhxpxo8fb+e/7LLLzIknnmj/7otbW265pZk5c2bOfMjlxEGRTpF06dOWSJc+O40UAREQgSgRkEgXpdMqMV8HDBhgFi5caMaNG2eaNGlSYrvXdkVABESgMAhIpEt8DitXrjR0vv3uu+9sOtrPP/9snn/+eTN79mw7mNRWfvFEfTf+8DqpaxdccEHBp/7xizL8xE466SSDqJQv+/DDD03Hjh1jy5133nnm3HPPzdfyeVnnoosuMvfdd59da9SoUaZXr17276T4tm/f3v596623tvcpihZMd+Vr0r1lqROQSJc6M40QAREQgSgSkEgXxVOTzyIgAiIgAiKQJwIS6dIDfeutt5qrrrrKDiYazKU0pjdb1Y1CQEJIwkgrJSUzXzZp0iQzdOhQuxz12RAMi03gQQB1df5uvPFGc/jhh9v9fvDBB+bQQw+1f4+ySEdU5gEHHBC7MqTxytIjIJEuPW4aJQIiIAJRIyCRLmonJn9FQAREQAREII8EfJFu1qxZimxOkj1R4KQvYogtt99+e5Ijyz9G5N16662XkThF5N4GG2yQ1vr33HOPLVSPEcVGNFu+jHVZH/vb3/5mTj/99IyX/vPPP20abyaWjTnc+tQWI+0Z48506NDB/p0U306dOtm/F6JIBwPqBdIMpWHDhnFxJivSkS7+5ptvmr333ls16+LQlEiXyU+txoqACIhAdAhIpIvOWclTERABERABEcg7AdI3hwwZYsW5YcOG5X39qC5477332m6dGCmbd9xxR9Jbefnll80zzzxjXn31VZv2iBFJhmjTt29fK4xUZtSTe+ihhwyi6uuvv27FFBpV7LLLLuaEE04wBx98cNK+4Pfll19unyeqjXpwuTZq0dHd9IorrjBPPfWUXY4OqDRSYG/uD11Ct99++0oFTMSkxx9/3MB03rx5lieiF80o6KRat27dhNtZvHixTUl97733zBtvvGHrD9KxlLIc++67b8LxH330kW38wFhE1+bNm5utttrK3osRI0ZY/zA6vbpmEe+++671EcPfsWPHWh+o2ctrpFAjaPGHNORatWol9AOmzEGUHn/o4rvHHnvYmordunUzO+ywQ8I5nn76aRv5x71ydRipmXfdddeF1g9ORqTjnp988sl2vmJMaU4INckHJNIlCUqPiYAIiEDECUiki/gByn0REAEREAEREIHCI3D//ffHUkMRdFxEWGWerl271txwww1WkIlnNE7gmXjRSz/++KMVOmbMmBF3DoQ+UliJ0Etkt9xyi7n66qvtYxdeeKE544wzEg3J6PU1a9ZYsSdeN9fg5Oxj4MCBoWt+9dVXNgLvxRdfDH0doevf//63FS/DDIGPlNvzzz8/7p5opnHllVeG1hZEbPzXv/5V6Xn6E/uNst566y1zxBFHJMVyu+22syIw4l+Y4Qf30UVExpv0tttui0XvBZ9BrEekd1F/YXM88MADpl27duVe8rvUwhuR0beHH364XHQmPvbv3z+pfZfaQxLpSu3EtV8REIFSJSCRrlRPXvsWAREQAREQARHIGQG/nto+++xjxaBERnosKY/O9ttvPxvdRASXa0LBa/Ei8xD5iL7yu6FSD69BgwY2ksxF5TEHEVyIdYkMkYmGBhjRbESP5dJovpFKx1uiPM8555wKLhGVBT9f7KN5ByKmz5KBiHhEtgXt7rvvLhc9uuOOOxoEMRed6J4nOtFFG/pz4JeLkkuGmd/tl9RPotuCRlRd06ZNKwiPRLPRXILowqDhW7KRnGEdhxH5iOL07w+C27bbbmsQE50RrUnEoC/+Eq3HOWC+SMddJfoOEdgZYik/Jzwnq0hAIp1uhQiIgAiUBgGJdKVxztqlCIiACIiACIhAHgkgzjjxiJRCIoYqs0WLFpWLQvr73/9uTjvttNgQX/Tjm8y/6667lpvyiSeeKJeOSsor6ZAYQguRUK6TKEIIYlMiQYSovjFjxtg5GN+vX7+cU0RQQhCaO3duuXRfUkvXX399U7NmTSsE1a9f3zYl4HtBI/rPCUAIa4ifTohDxDzqqKNi6ZoImzfffHO5KUgNJcXYGedBxB6NK0i3pYGGL7w+++yzBhHPGSmcRx99dOzrzTff3I7hGQQ4zvO1114rt+aTTz5pdt55Z/u9OXPmmB49esRex0f4uwjKX3/91c43efLk2DPs+dhjjy03p9+AghcQ0q6//np719gHadV+x9wHH3zQtG3bttwcfl1CXiB6kWg30q6DkXB+XT2e9UU61uZMqZE4aNAgM3Xq1Ng6RE+OHz/ebLTRRjm/X1FdAGEdZjBu2bJlVLchv0VABERABBIQkEinKyICIiACIiACIiACWSaA+OFENiKEENAqM4QPJ6Ah5CD6BI0otmnTptlvBzvGIrggWCGKYNRbczXx3DzUQ9t9991j4hQ13/r06VOpXwg6//znP+0zI0eOtPXP8mV0xL322mvtcqnUKvOFIcZSR22nnXaKuU0aKw0bHn30Ufu9sMYMiHKkb2JhjT+Ctdbo5kuknjO4zpw5036JOMV5brbZZrHXiSTDBz/Szhf6fJEOkTEsfZl99OzZ09a6w4L3jNcRCp0YiB//+c9/KtThQyCjbiFGNB48nBHZSJ08V38uKB4H7xTRoCeeeGJs/MKFC2N1+xAqp0yZYoVePwKPtF6iNcPE1nzdNa0jAiIgAiIgAoVCQCJdoZyE/KhAgJQJIgv4B6hMBERABERABKJE4LnnnotFncUT3fz9kBLoBLZ4dbmIonH114LC0tdffx2LmmNexJCysrIKyBDaiFjCKNY/fPjwSrEinpDyigUFmFyfh998g86u1JdLxvyIQl9gQxijmQYRdn7K65lnnmkuuOCCclP75+GLZ0TYEQVHqqZvRIghgjkj0skJWzzrR9W5Z4hupJvrp59+ar+FEIcgh/kiXatWrWINNIL7R3TjHJ1RA86Z3yGW7xEt6JpR+PO4NEq+R804P7rSbxzCnUMkrlGjRjk3aO5BrUJ8p/kFYpzvj2uGwfd4zQmCfI2Yyb0iQlEmAiIgAiIgAiJgjEQ63YKCJECBYvfhwi+kXJDOyikREAEREAERCBB46aWXbCdVLCxSy38csWabbbaJfSusLhgvBpsJEM1VrVo1O47UVf+XWgsWLAitT+aLLu3bt48JdvEOkEg2ItqwfIt0RLqRFokRwYfAmIz50X90pKV7KRFiRK35AhFzUS/wrrvusim0zn755ZdynU45S35xiFiHKBa0O++80xxyyCGxb1MHj4hFZ6S3brLJJqGu9+rVKxbp5kexJSvSBdei82vt2rXtWkRmEqGJhTVt4PvBvfoiH6/DD1ESIy2WiMYwI6LOZ+ieCUYcBsemcq7JnL2eEQEREAEREIGoE5BIF/UTLFL/+ccwHdMwiXRFesjalgiIgAgUMQG/JhnRQ/x/LZ4F0zMZ26hRowqPB+vWvf3222bjjTe2zyHskT6J0UTApVoGJ/GFr8oitNw4v7Zbss0msnWs06dPt2m7GGKWa2CRaH4/LTjes0S9kbpJ3Tdqq/lGo47DDjss0TI2Ko3oPnj7RldZv65bUPjyn6U5BCIe5jewSFakY5wfCUfqK41CMGrY0fwCI6WVf08FjUYarg5emJDHHhH+sNtvv92m/qZiiUQ65qLzLPUGZSIgAiIgAiIgAoqk0x0oUAIS6Qr0YOSWCIhASRIgUqhx48Ypf0AvSVj/v2m/O6crmB+PB00SiGpzhkBDU4Sg+f9v5DU/NZH6aYhOWGWRe9SXI9IMS6ZW3jXXXBNrqkCNOyea5eNsX3nlFXPMMcfYpYI1+Cpbn6YQrk5b8Dn2TE006sfFq4FGJ9zjjz8+7hKklxIl6Uc/+g8HIyNp3lCrVq3Q+ajH5uqzxUt3reycfvjhB3uOzj777LNY6ihRiK7uHr/4dPX9fEf8brpBkY46h82bN489jvAbFCQT3QNSeQ866KDYY6xB5CKpty+88IL9Pj8fpHI7cTHRnHpdBERABERABIqZgCLpivl0I7w3iXQRPjy5LgIiUFQE/Pfjd955x9SpU6eo9perzfj1wOKlGrq16XbpdwaNF1nkC2xB4S8oLAVri7m1/PTKZKLT/Jp0pE66mni54ubP66f3HnzwwVbcScboqus3ZCCSkb0iiLmab5XN88knn5RLX+VZRFSi7vAjnuDmz8nziK9YsPOr/5wvKD722GNmt912sy/7kXR8j9fCjKYQ7A0L1j5ETHTpuX379jVEQgYt2BHYT5MOdriNJx5XxtIX6fg54Fw4g6AwTaQf937ddddN5oj1jAiIgAiIgAgULQGJdEV7tNHemES6aJ+fvBcBESgeAno/Tu8sg0JPZSmPrOB32CSFkkYJQfMFto4dOxrqyznzu2jyvbC6dsH6Y6RDElVWmY0ZM8aMHTvWPhLPr/QIJR7lC53x0jXDZqFRw4033mhfIj2TzqthjQmIeCN6jajFPfbYIzYVDR9o/OCMKK8ddtgh1GGi5BC2aDThC9hnn312rKMv3U6p5xc0xiH6OaPpgmuy4Edi4tvDDz8cuj4dhOkkjHXv3j12VnxNMwyX4hom9FFHjohC17iCMX4DjF9//dW0aNEitm5l5UeIiiO1FR9cCjYDP/zwQ8NdxYIRgUTo+sLhWWedZc4///zEF0NPiIAIiIAIiEARE5BIV8SHG+Wt6UNhlE9PvouACBQTAb0fp3eawTS/RCLd5ZdfHhPdEGUQRPyoomCDAMQMRA1nf/75pxVcELawsG6ofsdZnpk8ebJtqlCZ0dnV1YKjiQDiU77Mr2eWTGqu8+vJJ5+MsSF6i9TXDTbYoJzbq1atsh1JqQOH0bV0++23jz3jd3e98MIL7bNB87vtEqXnuuDyHGsSJecsWM/t22+/Nccee2ws2o7nqP/H97B58+aZI4880v6dSMCHHnqoQqqp3/2W5/xIPL4Ovu6n03Jf6CLMM74FuwKTqupEPPwhmtM1K3Hj/A6zwWYkfn2/YBo2PpA+jV/Ogk048nXXorAO0bH8QfRURHMUTkw+ioAIiEB6BCTSpcdNo3JMQB8KcwxY04uACIhAkgT0fpwkqMBjwSgpv1ZY2Ixff/212XvvvWMvEQFGaikpjIhVREW5Av4IT7NmzTL16tUrNxVplaeeemrsewhqFP6njhjdXxGaiBLD9tprr1jXTjcAIQjRiggrrEaNGrbzKAIhhlCGeLXeeutZAZH/EuHmurGnR6r8KOqg0eUUYWjt2rXmqquusg+Q3svf8Yl1+UPDg7COokTI0YjAdXJFXKIzbN26dW03UxpSEG1Hww5nfM+PGoOFi+qCNzXU2DtNJoiSJPWW7qnOwmrm+dF0PIeABSsEOmrFubNwc5CeOnz4cPtlsJMv3+vTp4+tg0eEGz+XrqYbr3FfEAJ98+vN8X3STBES2QORhn5KsBuHIOvSZ/me3w2YrxERqW8HK+4lTU78aLhgCrWfthvWQIXGFbBzZwFrRLstttgiG9epqOZo166doXlM8IyKapPajAiIgAiIgJFIp0tQkAT0obAgj0VOiYAIlCABvR+nd+h+mh8zfPTRR3EbFbgVbrrpptDi/kEP4jVwQNRC6HHRYZV5jkCz6667xh4JpsImu+tEnWuTncc9R91DRJtk7IADDqgQCebG+d1u3fcQ+pzg6M9PN9iLL7643JK//fabTUX1hTweQEQKimvMi6i37bbblpuDmm4nnXRSLLoxbE9El7lINb/uXrIdZpmTOUiVbdKkSYUlgiJb8AHOD/+dAExkG/fLGYIgnJ3gmehciNb0Obz00ku2yYZjRyRY0II/K4iqN9xwQ6KlSu5118WXhiCuk3PJQdCGRUAERKAECEikK4FDjuIW+UccaTtYZTVQorg3+SwCIiACUSIgkS6901qxYkUswoyoNUScYJpg2MyILUHByH+ODp1HH3103LkQl6gdRyprmBFVR505vwabe65Tp06VCkph81VWLy0dcn4dukTjiWzzo9mCzxOthqBRmRGdd9xxx4U+gqBH9CE/A/GM6MJx48aZzTbbLPQRRC7WCDa9QBwjjRZBy4mSvvjCOTI3giDpjURNuvpy/kIIWsyPeBhmpJQi/hI5GDTGkCJLTTvX8TesQQfRW3BwXWjD1kEoJDpvp512Kvfy22+/bQ4//HD7vcq6Dj/99NOxOowS6cJvm0S6RO8Iel0EREAEioOARLriOMei3AXpFBTC5oNN2G+Hi3LT2pQIiIAIFBgBiXTpHwhRWERJIdIFa6JVNiv16+BOiiqdX5s3b24FjrZt2yaVBogwQ0QacyCskCJKmiRzUGMsni+kiX711VeGlFPm4A9/d3/c10Ts8T1STanjloz4mApFosj4ZR0CFz659ViHBhCka1KTi72QwlqZwZ/OtzRiQGzief4gJh1yyCGmadOmlY5nfaLD4Ei0GftGMGvYsKFNqSUFEb6JjL2wJ9KaSXn1/11D+uvKlSvt+fjGWfDvICIe119/fSvYkWLKvcIH5oknzgX9Ie2UlN6ZM2fac2NOIggbNWpkowsRPJk/WOvQzbNmzRrz1FNP2a6z1NuDS+PGjQ3CEcIeLOJ1ZkVcpJsrNfr8LsZBH0nfpXHF8ccfb/nKyhOQSKcbIQIiIAKlQUAiXWmcs3YpAiIgAiIgAmkRkEiXFjYNEoFIEUB0I/pzk002iZTfpeSsRLpSOm3tVQREoJQJSKQr5dPX3kVABERABEQgAQFfpCMtrmXLlmImAiIgAiKQZwIS6fIMXMuJgAiIQBURkEhXReC1rAiIgAiIgAhEgQDRNdRAIy2QIvQyERABERCB/BOQSJd/5lpRBERABKqCgES6qqCuNUVABERABERABERABERABEQgSQIS6ZIEpcdEQAREIOIEJNJF/ADlvgiIgAiIgAiIgAiIgAiIQHETkEhX3Oer3YmACIiAIyCRTndBBERABERABERABERABERABAqYwIgRI8zUqVPNuHHjVBu0gM9JromACIhApgQk0mVKUONFQAREQAREQAQyIvDtt9+aadOmmenTp5sNNtjA3HzzzRnNp8EiIAIiIAIiIAIiIAIiEEUCEumieGol4jMdBRctWmR69uxZIjvWNkVABESgdAisXbvWinJOnKNBhbMvvviidEBopyIgAiIgAiIgAiIgAiLw/wQk0ukqFCQBPqyVlZVZ3yZOnGjatGlTkH7KKREQAREQgdQIvPbaazFx7vPPP48NbtSokWnfvr39c9BBB6U2qZ4WAREQAREQAREQAREQgSIgIJGuCA6xGLdAFF3v3r0l0hXj4WpPIiACJUdgwYIFsYi5OXPmxPZfvXp106VLl5g4t+GGG5YcG21YBERABERABERABERABBwBiXS6CwVJQCJdQR6LnBIBEShRAnfeeadp3LixOfTQQ5MmsHz58nLprP7AAw88MCbMbb755knPqQdFQAREQAREQAREQAREoJgJSKQr5tON8N4k0kX48OS6CIhAURHw34/feecdU6dOnUr3N2PGjFjU3LJly2LPtmzZ0nTt2tWKc9tvv31RMdJmREAEREAEREAEREAERCAbBCTSZYOi5sg6AYl0WUeqCUVABEQgLQLJvB/PnTs3FjX3ySefxNapX7++6dGjh+nYsaPZc88901pfg0RABERABERABERABESgVAhIpCuVk47YPpP5UBixLcm/dV/JAAAgAElEQVRdERABEYgkgXjvx3RgdZ1ZX3311XJ769atmzniiCPMIYccEsk9y2kREAERKDQC8+fPN/zhlx6JIpoLzXf5IwIiIAIikDwBiXTJs9KTeSQgkS6PsLWUCIiACFRCwH8/vueee8yjjz5qFi5caObNm2fWrl0bG9mqVSuz//77m7322svUqlVLTEVABERABLJEYNNNNzV9+/Y1ixYtMqNGjTK9evXK0syaRgREQAREoNAISKQrtBORP5aARDpdBBEQAREoDAL++zHNIxYvXlwYjskLERABEShBAoMGDTKDBw8uwZ1ryyIgAiJQGgQk0pXGOUdul4Tzd+7c2fo9ceJE06ZNm8jtQQ6LgAiIQDEQ8EW6gw46yLz00kvlIujWWWcdQ+25Bg0amNq1axfDlrUHERABESgoAi1atDD33nuv9UkiXUEdjZwRAREQgawTkEiXdaSaMFsEOnXqZMP6n332WdOkSZNsTat5REAEREAEUiAQFtk8e/ZsW4+OP35kHe/VRx11lDnssMPMDjvskMIqelQEREAERKAyAs2aNZNIpysiAiIgAiVAQCJdCRyytigCIiACIiAC6RKorPzA77//bp5++mkzdepUK9itWbMmtszuu+9uunfvbtq3b2+22GKLdJfXOBEQAREQAWOMRDpdAxEQAREoDQIS6UrjnLVLERABERABEUiLgC/SPfPMM6Zly5ah8yxdutRMmTLFinWM8Y3IaEoYINhttNFGafmhQSIgAiJQygQk0pXy6WvvIiACpURAIl0pnbb2KgIiIAIiIAIpEqDswCmnnGKaNm1q7rjjjqRGU1f0iSeesILdggULYmM23HBD061bNyvWHXzwwUnNpYdEQAREQAQUSac7IAIiIAKlQkAiXamctPYpAiIgAiIgAlVAYObMmebxxx+3KbErVqyIedC8eXNDhB2C3R577FEFnmlJERABEYgOAUXSRees5KkIiIAIZEJAIl0m9DRWBERABERABEQgaQKPPfaYefTRR80LL7xQbkzr1q2tWMcfuhjKREAEREAEyhOQSKcbIQIiIAKlQUAiXWmcs3YpAiIgAiIgAgVDYNmyZVase+SRR8y7775bzq8uXbqYm2++uWB8lSMiIAIiUAgEBgwYYF555RXz0EMPxa0NWgh+ygcREAEREIHMCEiky4yfRouACIiACIiACGRA4OOPP44JdkuWLLEzffHFFxnMqKEiIAIiIAIiIAIiIAIiEE0CEumieW4l4TX1ixYvXmz69etXEvvVJkVABESg1Am4rrBt2rQpdRTavwiIgAiIgAiIgAiIQAkSkEhXgocehS1TXLysrMy6OnHiRKMPbFE4NfkoAiIgAiIgAiIgAiIgAiIgAiIgAiKQLgGJdOmS07icEiCaonfv3hLpckpZk4uACIiACIiACIiACIiACIiACIiACBQKAYl0hXIS8qMcAYl0uhAiIAIiUDgERo4caZo0aaLyA4VzJPJEBERABERABERABESgCAlIpCvCQy2GLUmkK4ZT1B5EQASKgYD/fjxr1iwr1slEQAREQAREQAREQAREQASyT0AiXfaZasYsEJBIlwWImkIEREAEskBA78dZgKgpREAEREAEREAEREAERCAJAhLpkoCkR/JPQB8K889cK4qACIhAGAG9H+teiIAIiEDVE5g/f77hT8eOHU2dOnWq3iF5IAIiIAIikBMCEulyglWTZkpAHwozJajxIiACIpAdAno/zg5HzSICIiACmRBo166dWbRokRk1apTp1atXJlNprAiIgAiIQAETkEhXwIdTyq7pQ2Epn772LgIiUEgE9H5cSKchX0RABEqVQLNmzezWBw0aZAYPHlyqGLRvERABESh6AhLpiv6Io7lBwvk7d+5snZ84caJp06ZNNDcir0VABEQg4gQk0kX8AOW+CIhAURCQSFcUx6hNiIAIiEBCAhLpEiLSA1VFoFOnTjas/9lnn1U3wao6BK0rAiJQ8gQk0pX8FRAAERCBAiAgka4ADkEuiIAIiEAeCEikywNkLSECIiACIlB6BCZMmGCuuuoqWztoxIgRkQSAQHfWWWeZb7/91vrfsmVLM3r0aPtfmQiIgAiIQP4ISKTLH2utJAIiIAJVSUAiXVXS19oiEIfATz/9ZJYuXWq23nrrtBkxHmvYsGHac/zxxx9myZIlpl69emaDDTaoMM+qVavMsmXLzKabbmo23HDDtNfRQBEoNgL87LRq1crws4x9/vnnplq1apHa5tixY82YMWOsz3UbNrb//WHpYlO7Th0z7NJLVbg8UqcpZ0VABKJOQCJd1E9Q/ouACIhAcgQk0iXHSU+JQN4IfP/992b33Xe365133nnm3HPPTXntF154wZx00kl2XLo1/RAVTjjhBPPll1/aeUg73nHHHWO+MO8FF1wQ+3ry5Mlmzz33TNlXDRCBYiSAOOdHm33xxReR2ubQoUPNpEmTrM9dT7vUtOvR3/59xoQx5rkJY+3f+/fvby699NJI7UvOioAIiEBUCUiki+rJyW8REAERSI2ARLrUeOlpEcg5gaeeesqcccYZdp099tjDPPzwwymveckll5h7773Xjku3Cxgfvu+5557Y2ieffLIZPnx47OsjjjjCvPXWW7Gv0xUUU96cBohABAj4YjtRpjTDiYKtWLHCINBNnTrV1Nywthk46iGz+TblU1vnTJtkJo8aardDKu+oUaOisDX5KAIiIAKRJiCRLtLHJ+dFQAREIGkCEumSRqUHRSA/BLIt0g0ePNgKdalaly5dzLvvvhsbtttuu5nHHnvMfv3LL7+YHXbYodyUxx13nK2/JRMBETA2Tdx1pSYdfO7cuQWPBYGud+/eVlCMJ9C5TSxZMN/cPvRos/qnlRLqCv5k5aAIiEAxEJBIVwynqD2IgAiIQGICEukSM9ITIpBXAs8884w57bTT7Jr77LOP+fe//53y+sOGDTN33323HUdUzNlnn53yHO4fg/7Azz77zKyzzjo2go5IOt86duxo7rjjjpTX0QARKEYCCxcuNPvuu6/d2pZbbmlmzpxZ0NtMRaALE+r69etneN+RiYAIiIAI5IbAgAEDzCuvvGLGjRsX+yVQblbSrCIgAiIgAlVJQCJdVdLX2iIQQmDatGmGf4hhBx98sLnrrrtS5nTZZZfZf8RhF198cWy+ZCf68ccfzc4771zh8ddee802onjooYfM+eefb18nlY/6W+mm5ibrU7af+/PPPyNXyD/IYPXq1Wa99dazwqmssAggaB944IHWKWo5UtOxUC0dgc7t5dO3/mvuOL+3/ZK0V9JfZSIgAiIgAiIgAiIgAiIgAukRkEiXHjeNygOB//73v2bRokWmZ8+eeVitcJZ47rnnDFEpGCmnN998c8rOXXnllea2226z4y6//HLbACIVe//9902nTp0qDHnkkUdM69at7ZxEzREhtP7665uPP/7YdqJ9/vnnU1kmqWepi/fEE0+Ybt26ldsHNb/eeOMN2wWXP4iHJ554YqVz8jxzvf322+bNN9+0XWkRQqkBmGwn3XfeecfWCfzkk09sWiBC2d577225HH/88bYTbiKjKcf06dPteLrjLl++3HzzzTdmzZo15sknnzSNG//VSTPMXn75ZUO05auvvmq5Y3vttZc9r759+5rq1auHjqOZyE033WSaN29u05IR9hYsWGAQXl9//XWzySab2HkOPfTQRO7b1+leSkTlf/7zH0NTBPbx3Xff2X2wBk0Hci0ecu733Xef+eCDD+wfmpwgFtPAhPsSTMnGb9hfccUV1n/E7C222MLeH+4G7zm//vqr2XXXXU337t1NrVq1KmVB2jcRcnPmzDEfffSRadCggdlqq63s+Pr165sOHTrY8bvssou9d4VomQh0bj9+jToJdYV4yvJJBERABERABERABEQgKgQk0kXlpErMTz44lpWV2V2n2500qsgQPWjSgCFQjh49OuWtIMLceuutdlw6H5oRghCcsP322y+WqnfDDTeYI4880ophL774ohW4EMsQa3JRHP+rr74ybdu2tX4w/3vvvWfmzZtnrr32WjN79uwKXIIdaN0DiClwrCwdlzmpxxXPiC5kDr+ZRvBZRMvx48ebFi1ahE6DMHfNNdfExLWwh/7xj3+YU089tcJLa9euNfAfO/avzpphRg00nkGwDBodgzkrjD1cf/315Rp/uOeDDUKC8yBu3XLLLXafbr4wX6hfSB3DXNjvv/9u7r///oSdRRGqg2LzkCFDDJ2IMaJMESrDUsoR++C00UYbhW4BIRtx99NPPw193UWY8iLnwvtYoVk2BDq3p1mPjDdTbh1p6tSpY/fqd7YttH3LHxEQAREQAREQAREQAREoVAIS6Qr1ZErcLyJanGBSyiJdnz59bNRPqnb11VdbIQX717/+VaF+XKL5EFjOPfdc+xg17Vz3RlffDtGBwviIdUQQcV4YgkW8SK5Ea4a9TrQbEVHOzjzzTBsNFs+uu+46c/TRR1d4mfRh0oidkYZImuisWbNsqq6zG2+80Rx++OEVxiOQUYPPb6RR2X6I6gpGYSFqjRw5MnSYL+jEq+3npzAzCeIpkWIIl75gGTYeUWubbbZJ+ggef/xxGw0WNKLMSHPm9aD5e+A16pO5iNCkF07yQRfJmczjLvrTPcv7iruvicbHSxWPF2kab74DDjgg1m050Zr5ej2bAp3zedJ1Q8zc6ZMl1OXrELWOCIiACIiACIiACIhA0RGQSFd0R1ocGyplkW7GjBmmf//+9iBPOeUUc8kll6R8qL6IQfQYwk0qxhjmwIhYclF1CGCk0m677bb2tQsvvNCm+uEzRkRd3bp1U1mq0mdfeumluKm6xx57rI1QIrqNNEfs73//e6zphpvYj0x0+3EF/YmOoyutE99If0XwqlmzZjm/HnjgATu3M6Ks4INIhtiBIOpEUZ4hDRUR0Fmw0QYRd+ecc45Nk+XvfopzWNowad/t2rWLzRfcJ6mlCKjOgiLbDz/8YFMug9aqVSvTo0cP06hRIyvEuqiweOKwfy+Yi8Ym3FWi9EiX9dOsE0XkpXtJEED9lFzOjKhA+BDlRyqwE5hZ48EHH4xFY/I1kXWIbL4xx0knnWS222478+ijj8YE3XgNH7h7vjDKWCJMqXNINCf3xRd/27dvbyMPC8VyIdC5vU0YPsDMnz3NRtLxCxYi62QiIAIiIAIiIAIiIAIiIALJEZBIlxwnPZVnAqUs0k2dOtUMHDjQEj/rrLNiDRpSOQIitpwoMGHCBLP//vunMtz4kXjUb3NNJBBliFZzgtE///lPQ60zhA2MFFhqcmXLqM8GA98QUogOpBg/5keYBVNFEU3YuxPxeDZYtw4h4YILLogtQW0yaos5I6WTqDUnupDiS1MOP2LQF9HC0n7x10UjIvwgHNaoUSO2BhFqpPWyVlj9sosuusjWXsPiNSHwowW7du1aLuIwKPIxDyIhYta6665r5/W7CpOmSjRl0Hxxiog0UoR9I6rvsMMOs98iFRQRN5vGeSIUU0cPQ1yDZVAYdpGePEOdRL/eoP8ar3OepBBvvPHGds5vv/3W1rVzFoyKRJRG2HTG3SHC0zdSshHtnHXu3DmWfp5NHunMlUuBDn9Wr1phbh96tFny6fsS6tI5II0RAREQAREQAREQAREoaQIS6Ur6+At386Us0tGU4LzzzrOH49JLUz0pxhFdhdGJlYitVAzhwdXQoikAIhVC1+abb27FBidAUMvrqaeeiglIFMcPi9hKZW3/WaL4EN6cuUin2rVrx77Hmmeffbb9Gl+IDnNGSi6iDIZ4huDoRCmiqe69914b9eQsTCDjGT+akXp9TZs2LbclIvFo8oGFzYGYSbSX84M0SlJuaVrgjOg7orBItw0KnY4/z1566aWxSEvfCV/cDUbjBdMzifwKpt5yzk7MjVdfkM6dTiDjLEh9ha8TuPCH6Ed4IKbRPCGbFtwHTVUcd3+dZs2axb6kOQf7cea/xl2hPl0wNdmv34cI6KcK+3eSnwcaR/iCq1vHv5ekSiPUVrXlWqBz+/OFOqIeb7/99qreutYXAREQAREQAREQAREQgUgQkEgXiWMqPSdLWaS7++67bT2vygSZRDfCj6qaMmVKrAlHonHudVIYSWElUmnu3LlWFHIpraQ8Mj9GIwREDtdJlkL7iE/ZMuYlhdLZK6+8Uk7Y4vukONLpFF+DDRv8Bhj49be//c1G+xGhF6wvx3jqlwUFMqKkYIgFI9ScX/46RGbddddd5RD4Ip7/gusui4h60EEHhYpawXpywRprbr5gSi1dTKtVq2Zf9qO/WBNhyReueIZIQb/YP7UG6dzr25133mlGjBhR4XgR7Ki7RndYhL5EXVHTvR9EExJViMUTEmkS4nd1RXx0xl2h86yzeD8biGrwxILpsn6UamXp6NzVY445xs5Bp9jKGn6kyyOVcfkS6JxPSxbMtxF1q39aaRB3XSRpKj7rWREQAREQgf8R4N/G/OKJpmIqJaCbIQIiIALFS0AiXfGebaR3VsoinR91lU5nVg7ej3hKJwXViRSIL4hzfvrroEGDYoIDAh6RaO4DuOv+mq3Lh7AxZswYO1069fl8wbMyn0ipPf3000M7eSKeuVptdAYlTTRoft07IruI8AoakY103a2sIyoRikSn+ZF6RDASSecMQZIackELprQSNegi3PzafpV1GvWjzMIE0dWrV9uz9+vvBf1APCOlmFTabIt1iNecKRZvH9QZdOnZQSHv559/jqVJMwedXV1kpb8PX+QONl7xU4/jRTUyl8+8qkWqfAt0jqUv1FXGKlvvF5pHBERABIqZQFlZma2Dm+6/DYuZjfYmAiIgAsVEQCJdMZ1mEe2llEU6UitJscRIE/OL5Cd7xH56JEIa0VOpmEv3owYdKa1+Ci5zE4mFffbZZzbV1aWDEmVEKmW2zG+AEa/TZmVrkWKK6BlmpCrS3IDfSFfGh+gyV48OgYqoqKCRpnrqqafab1eW2khUHCIbXWURT8O6xeILqcYIpBhpsDQecEZUXFgaqf8zw7N+mqefCktEIRGPYebXa6ssdZkPCeyBCEKaXpBWHDTqunGPgxF7mdwNBGJX/zCsJh5zf/fdd6Z169Z2maBIh0DK3XbmR9n5ftGYw6VBB+8d6d6IrRhCpEtND+6LWo3uZ6Eq012rSqCL3ddpk8zkUX81NdEHy0xuv8aKgAiUOgH3izT+Xzh48OBSx6H9i4AIiEDREpBIV7RHG+2NITBQbB1DsHB1xaK9q+S8p2kEogqGQIZQlqr5EVFhaYuVzeenVxLZRXTcm2++abp161ZumKt75tfeyvY/HIm+cYISEWbBJhKJuMCPFFdniDYIJuxlzz33LNf8Id5cPksEGncv/ef96CpETNfkIZF/RH3RqIIUVpdSyxg6zjohKBj9RU00153Wn9+PwHRpyu51vwFHZf7BhbPGSG095JBDEm3Bvv7VV19Z0Y7UUPbjLNuRlYiqRC1iffv2DU299e8jz/nRcl9//XW5+oyIzOuss06FPSImuRpyiK9+XURf8KysIUQw1TqeMJoU4DQfqmqBzrk9xxPqSu39PM2j0zAREAERqEBAIp0uhQiIgAiUBgGJdKVxzpHcZadOnQwpfEQpNWnSJJJ7SMdpvx5WOo0YVq1aZXbaaafY0vGiheL55kciuRRTP4XQjevYsaOhPp0fMdSnTx9zxRVXpLPt0DF+51bSUX3BLZlF/JRDBDqiCmvWrBk6lAi3H374wXTo0KGccONHl9GggqYcviH0+HX4XIqw/wypo9xlmkLEW59UWur7YcFUTt8HGMAiaH6Kszsb94wf6UezBBpshJmf5hnshIt4SwdY6tQxf5hR840IOpfSGy89OJmzC3vGb2gS1oGWdFyEM5eezBx+JKl/t3mNSEa/CYlb06+9F0xfDkY2hqUFM4/fvCVet9x0OSQ7jmhDIixrbljbDBz1kNl8m5bJDs36c1NuGWFmPXqnraOEUOfXP8z6YppQBERABIqQgES6IjxUbUkEREAEQghIpNO1EIECI+CnV1IPzqU9hrlJlBUiHF1CXf0xIodoXoDFK67vz7Vs2TIbCUWxfepz+R00EUVonID5HS/52olm8+bNi3V7DWuakAleIrFGjx5tp0hHAGRfbdu2jbkQ1nQBYYm0WBc5RQQbkWzOTjvtNCtOYaTIIko6oY00WLqYBtNWEYmqV69ux7z++us2pRZDzBs/fnyFOmgwP+qoo2JptcEUSz/tFxEMkcOvpRZM4wxGHfpRXewB4SbM/FTrYA3Am266yVx77bV2mH8v/Hkee+wxmwLq7PHHHze77rprJleg3Nhgp13/5+PPP/+0nW9dqrgb6DeHCDaViCewIWKeccYZdoow0ZW76FK+iXQlLd0X+4J+JvNzmDVI/z+REwkLQaBze5t03RAzd/pkCXXZPmzNJwIiUBIEJNKVxDFrkyIgAiJgJNLpEohAARFYs2ZNOVHuwgsvtE0CEOOIZlu+fLmNUkJ8QpxztcAQXhBiEG6Ctcmoo/bbb78ZoowYz59vv/3WLFy40HzyyScxYcgVt/e7UhIVhyCB+amGfE1Dhx49elgfXDrylltuGRMvsoGVumDUB8MqSy2sbC3qtiDOYTvuuKNBbNpmm23M2rVrrYBGmujs2bNjU9BN9vjjj4997Ufj8U1SgBGpOANEIQS2oPnNOqZNmxbrhstzCGEIYBhReAhuwUYMr732mmnYsGFs2mCaJnUKSYtmP3RxxR8nFCIIkXpar1692Pj33nvPHHbYYbGv40VX+kIcayA+OfOjGvmeE+AQOYlWI/rMj9ALE7cyvRPBSDjWQFxFEL3xxhutT0EL1kHz05effvrpclGnbiwpu4imzoK8Pvzww3LRhPz8EV1IlBgRmZxf0OLVEsyUSdh4OvByHoUk0Dk/nVBHdDTitzoU5uIGaE4REIFiJCCRrhhPVXsSAREQgYoEJNLpVohAARH45ptvbK20dMwJOwgPYemQieZ0AhtiAuIb5tdgCzZhcAIHYhf16ZwhGlWrVi3Rckm9TlOCfv362WeJIKOBRaqGEBmsrYaQ5ZpB+PPttddetntosNlBUKAM+kCEHBF2zkgDdimhwSg3nom3Pq8hNpEWGzRfQKuMgS8CuueWLl1q2JuzDz74ILTzKmKmK0bN83SkdeanNbvvxdsHNfGoB7j99tunelwJn4ctkYXxDMGM9Z1oGYwI9JuqxKvvF+yoS4rreuutV25Jaswh0sYzfib8tNt0UtcTwgh5wNXMK0SBzrl7+9De5rO3/xu3Q286+9YYERABESh2AhLpiv2EtT8REAER+IuARDrdBBEoIALBdLxEriFGNG/e3Ka3urTUsCYPlc2DqNGiRQtzwgkn2HpspL/SmAARy6/n5Yt3CHrPP/98LOWSiCui7rJde8sXS3bZZReD0JGOIdiceOKJsVppYXMce+yxhmixGjVqVHgZFohXrqGH/wDRbIiHNDJwEVTBdFU/IjCe/zBlfb++XfDZCRMmGOaOZ6Sjkn4bFEkRUhF/Xa24eM1E/Ig91zTErUU6KQxcd9V4PiCmkqK81VZbpXNUCcfgB4LlddddV+FZRENSbonQQlTGginYfmQlIqQvXvp7ZRwiGz9jRNaFNZjgZ+2cc84x3FPf6MbL+qQdc2fwi/TYVLssJ4QReIBGEe3atTP8t+fQUaZ1x16pTpGX51evWmH+eXon88PSxer4mhfiWkQERKAYCEikK4ZT1B5EQAREIDEBiXSJGekJEcgrAWrKIYiRwodgRKF+/lAHbaONNor9IU0sGN2Do4gYpNwhHJD+yhyMZY5atWqVm4M6Wn5tM7dRxBq+X79+/XJ7JyJr5cqVBkHJX5uURwSNxo0bh0ZoZQKQiKy3337bpplm0uUX8ZFoMGroka4Ik0022cSKSQhjiICVGUIXqaukv5ImSxoyUVmIf3AlZRahDwuL0CLllMhAhDwn2CCw8qdr1652LlfHrjI/SL0kpRkfSINmPFFb1N6jNmE8I40ZwQjxaf/994/7HM/gIym/foSkG0B3VfbKfIif3AU+OBA1R+09RMt8GD8j06dPtyw5S2rf0fiCc0GMhCfiarA+H5GeiJ1wY4/xoj45LyILDzrooNBuuv4eSX2GBXUhuUeuZiHNNvi5wKd8pHUiOlKLruU+Hc0Jw+/IxzGkvcanb/3X3HF+b9tAwtV8THsyDRQBERCBEiAgka4EDllbFAEREAFF0ukOiIAIiED2CBAJiZiHmCqrWgIIZESUIcSWilEnkhqU7br3M11PH1bQ216+dJG59oR2tuFGsPFKQTsu50RABESgigjwiyh+QTZu3LiMfmlZRe5rWREQAREQgSQJKJIuSVB6TAREQAREQAQKmcCiRYtsumutjeqYs295xtRr2KRg3Z0wfKCZP3uqjb50HZwL1lk5JgIiIAIiIAIiIAIiIAJ5IiCRLk+gtUzqBEjp40MnH+JkIiACIiACiQm4zq6bb9PSDLxuoqm5UZ3Eg/L8xJxpk8zkUUNtFB2p0/lIBc7zFrWcCIiACIiACIiACIiACKRFQCJdWtg0KNcESFMrKyuzy0ycOFFh/bkGrvlFQASKggDvnTQPef/9903LfQ41Jwy/vaD25QQ6vbcX1LHIGREQAREQAREQAREQgQIhIJGuQA5CbpQnQBRd7969JdLpYoiACIhAigQQ6vbZZx/b5IUOr3R6LQRbsmC+ueH0ztaVSy+91PTv378Q3JIPIiACIiACIiACIiACIlAwBCTSFcxRyBGfgEQ63QcREAERSJ/A/PnzbURdoQh1CHS3n9/brF61QnXo0j9WjRQBERABERABERABEShyAhLpivyAo7o9iXRRPTn5LQIiUCgEfKFu613amBOG3VElNeok0BXKjZAfIiACIiACIiACIiAChU5AIl2hn1CJ+ieRrkQPXtsWARHIKsUTIRkAACAASURBVAFfqKuKZhIS6LJ6nJpMBERABERABERABESgyAlIpCvyA47q9iTSRfXk5LcIiEChEaBL9imnnGKbSdDtla6vCHa5Ngl0uSas+UVABEqJAP825hcvPXv2VFfsUjp47VUERKDkCEikK7kjj8aGJdJF45zkpQiIQDQI+F1f8yHUSaCLxr2QlyIgAtEhUFZWZngvHzVqlOnVq1d0HJenIiACIiACKRGQSJcSLj2cLwIS6fJFWuuIgAiUEoEhQ4aYyZMn2y3T9ZXur9k2CXTZJqr5REAERMCYZs2aWQyDBg0ygwcPFhIREAEREIEiJSCRrkgPNurbIpy/c+fOdhsTJ040bdq0ifqW5L8IiIAIFAQBX6jrevow0657v6z5JYEuayg1kQiIgAiUIyCRThdCBERABEqDgES60jjnSO6yU6dOhlpKzz77rGnSpEkk9yCnRUAERKAQCUyaNMkMHTrUukY0HVF1mZoEukwJarwIiIAIxCcgkU63QwREQARKg4BEutI4Z+1SBERABERABMoRQKgbMWKEWblypWm5z6Gm19BRtrFEOiaBLh1qGiMCIiACyROQSJc8Kz0pAiIgAlEmIJEuyqcn30VABERABEQgAwKUFjj66KOtUEfHVzq/pirUSaDL4AA0VAREQASSJCCRLklQekwEREAEIk5AIl3ED1DuVx2BCRMmmKuuusp22CIapVRtzpw5ZsCAAWbzzTc3jz/+uFl33XVLFYX2LQKRJIBQd95555n333/fCnW9ho62/03GJNAlQ0nPiIAIiEDmBCTSZc5QM4iACIhAFAhIpIvCKcnHgiPwxx9/mFatWpmffvrJ+vb555+batWqFZyfvkO///67mT17ttlwww3N7rvvnjV/zzjjDPPUU0/ZpZ588kmz8847FzQHOScCuSDw1ltvmeXLl5u2bdua9ddfPxdL5HTOFStW2Ig6hDoi6YioSyTUzZk2yUy5daRZvWqF6dmzpxk9enROfdTkIiACIlDKBCTSlfLpa+8iIAKlREAiXSmdtvaaNQKIcy1b/i/S5Isvvsja3LmYCH+PPPJI8/HHH9vpd9llFxv1lg1h8YgjjjAIFNhjjz1mdtttt1xsQXNmicAjjzxiFixYYI466iiz9dZbZ2nW6E3z5ptv2p+BQw891AprmRgNGKjvhiGCP/fcczayNGqGUEfn12nTpiUU6hDoJo/6q/GEBLqonbT8FQERiCIBiXRRPDX5LAIiIAKpE5BIlzozjRAB8/3339toNPehnHSxQrZx48aZyy67rJyLiDWtW7fO2O327dvHxD868e64444Zz6kJckPgl19+MTvssEPs3r733ntZEWpz421uZ0WkfOONN+wiM2bMMNttt11aC7799tvm8MMPLzf2wgsvNESYRtUQ6iZPnmyFOppJ0FTCN1+g69evnxk2bFhUtyq/RUAERCAyBHr37m3++9//mokTJ5o2bdpExm85KgIiIAIikBoBiXSp8dLTImAJLFmyJPYPpE033dTMnTu3oMkQ5UO0j29Ey2y//fYZ+73ffvuZL7/80s7z4osvmq222irjOTVBbggEI0A/+OADU6tWrdwsVuCz+hGg999/v9l3333T8phU9wMOOKDc2CuuuML06dMnrfkKZZAT6vCn/QmDzSEnDLJpraS3ItJho0aNsjU5ZSIgAiIgAiIgAiIgAiIgAtkhIJEuOxw1Sw4I8NvCRYsW2VSqQrOFCxfGPtRvueWWZubMmYXmYjl/EGc6deoUE9O6d+9uxo4dmxWf+W0uoiX26quvmkaNGmVlXk2SfQLUUmzevHls4lIW6RDR3M9tJiIdMM8++2zzxBNPWK5E5BGlWqdOnewfYJ5n9MX9eg2bmF9+WmGFuo1q1zbXjx5tU4VlIiACIiACIiACIiACIiAC2SMgkS57LDVTFglQG6msrMzOWIhh/Z999pk58MADrX+kd5LmmYz9+eefGaUX0vwBgZDovVRFAMYiom288ca26UW2jLRf0n+xefPmmXr16iWcOlMOCReI0AP5ZuFq2oCI2nTF0o2XVF7E4saNGyfVuGHgwIFm6tSp9qY89NBDZu+9987o1rz77rtm5cqVZs8990yb6erVq816661n1llnnYx8yeZgUvnpXs0vTbCOHTva9NYmTZpkcxnNJQIiIAIiIAIiIAIiIAIiYIyRSKdrUJAE+EBI7Q2sqkQ6PvQTaTNnzhzz0UcfmQYNGthUzl133dXUr1/fdOjQwfpHEwYXRROEiQBDcfqXX37ZClg0bqBYf5cuXcwpp5xi6tatm5A/4todd9xh62a5GloMIs30qquuMk2bNo07B2NXrVplfv75Z7NmzRpDJBWdJxEykjX2gLj3+uuvG+pvkR5JNFaLFi0M9ehoFOG63PKBnsL5YYbvcGIOivYjNB588MG2dleyDQyWLVtmXnjhBSsY0EmTr7/55hsrEt5www3Wn2zbr7/+akUJzo4UwH322ccyJcXZRXsienbt2tVsscUWCZdfvHixue+++wz14GACOwTfAQMGxE25RHwilZiUzMrEka+++soQFQbXYL1BOLm1nJOcBaJQjRo10haWEm44zgPcK8Tt559/3oqFdBVFeN5rr/9r7zygJSnKv12ABJEFlhx2BWQlL64EcV0EEQmLIDlnkCQZJIMgkpPknEGSJCWDoKCAAgqIICBBBGTJS5Ao8p2nz/+d75261T09M33vnbnze8/ZA/dOd3XVU9V9p379hm9koeRUGm0kIDLvJ510UnjggQey880233zzQF641FrkBcAbb7wRfvKTn9Q86S666KLsurBodE27BvcSPFkLdm9RiIX5KdsGbfFsuOWWW7J7zAq70Bc8X7fYYosw2WSTJQlyH5x22mnZvchzAGEPjrDgXp1hhhmyMVXl7YZXMyZxrtUVr/NEQAREQAREQAREQAREoDEBiXSNGemIQSAw2CIdG37Eo+eeey45ejb/JkwhKCAkxoZgsu+++2biSspo4/LLL89Evjzj+rvttlutemp8HEIXG/xZZ521TxM33XRTbvJ6BNBjjjmm4cwihO29995ZtceUcX3zouPzlGcWYufxxx+fCY15Rl9MlE0d88wzz4RDDjmkMKwYoQuxpWrzIX94ESHO7rXXXn0uA4srrrgiEy9ThihFW6lz7XgYHHHEEX1EHgQbE6FOOeWUQD612J566qnMywljbeHZZR5ZF198cTjooIMaouG8qaaaKvOcioshNDy5iQNYJwifRWHizCfCK56fKUOk2mOPPerWnz8OEfvCCy+sY5kq8pDXbVhsuOGGSW70n1xsfu1bOwjO3C8In0X22WefZeMrCjvn2cIxqfvbe7Cy7k844YTkc2LLLbfM7p12DGGTfiLQUShCJgIiIAIiIAIiIAIiIAIi0D8EJNL1D1e12iaBwRTpEEMQRcoaSeMRQbwh4CES+E38+PHjwzvvvBPuu+++umPzii1QjIE2vJH/Dk8487jhM7zyTj/99D7dPfDAA8Mll1ySO4wXXnihcIiIa8stt1wt31wZHiTRx5vIGx5iXuRDfMFj6d57760JnRx/6qmnJoUh1gLCgImivm0vlvJ7RM08z6My/U8dg0iCyFjG8GC74IILkociGPkqmIRJk78MryfL6ceJm266aTjssMPq2kAQwkPKLPYuRUxlfVk7cQg2Ik1ev1KdXX311TNxqD9swoQJpUNLU/cWfUoJ0Ix54sSJdSzhCE8zPPe222670sNifaUqN99www1hp512ym2nTJVjqi1TddmMe53Ku3hY+mcEwmsscOMhO++885YeB968eAC3av55zH0rb7pWSeo8ERABERABERABERABESgmIJFOK6QjCQymSIf3jN8kEzqHaGHheZdddlmdYESI5XnnnVfH8aijjgpnnHFG9juEGDbjVvUUEXDttdeutZEnsvmcWYgFCHGWB49KrXhlmRF6iSeXNwQz+kqeK7x6Pv3005qnWZ744M/HY4vqjWaEeSJw4NWDFxNtW1VXOyYW/u66666AJ4+ZT9CPYLnRRhtlHl8Y/Yc7nlxm9HnUqFG1n+n3jjvumIVzwpUcYF58IDSZUOQqDaEn5QVIKCLeTHiwEXZodv/99/cJe3311Vez0EOz/fbbLzC/eLoRNrn//vtnXpVmschDWCxrxgwOeFCSX47z6Yv32IzPR7wkxJbw4Ouuu67WDkVZ8Oiyf7RFODNrvh1Rp4i/L7LAcRRw2GWXXbJ1xXrC44/1hcHMr3N+FwvghBqzVvFgQ1heZZVVah6wsVhJaOpZZ52ViXleWCckFKaIX7CAA3ODWJ/yWqQP559/fhZqzb3Fsf650KhyMqGj48aNq1sP22+/fe3nuBpzLLLR/5QHLizWWmutrHgL9655AsOYirOt2mA+j1vts84TAREQAREQAREQAREQgW4kIJGuG2etB/o8WJtCRB42uWaEeiIKeSO3HKKdGR5MZ555Zu3n2APu5ptvDgsvvHDtc8S+3XffvSaWIC6Ql8vbPffcU+cBRLVIn2Ms7kMZzx0ELSsYgSCGsJdn5GHzYZuIYmeffXZdCB+CD3nDvFefF+kY5zLLLFMT8vAc2myzzeouiUcYjM0Qo8j9Z4b3GF5kZoRH4k3oDXEDwQpD8Bs2bFildwj98+HMs88+eyZ4efEQj0MTRFKVQhHlEHEwBCFYekNQxWvMjPXEuvJ2xx13ZHkMzRApEW/wliQnmRkiVJ4nKGHDyy+/fHboYFQlRoRFBDeDixen+D0iIiHeWKoKMeITohyGsIYo6kNiEVTNE7FIjF5ooYVqQnkVVYkR201wTq1TP5cHHHBAtoawvMIz3gOVfIdeCI5FPtpB6Nx1111r4b3cE8aWvJHXX399y/fFYD2PW+6wThQBERCBIUgAz27+4WHdbPGwIYhDQxIBERCBIUtAIt2QndruHthgbQoRWPBqwhBj2GyncktRAAGPIAxPGxMN+Nl/5gUZPHQIFcPDznvqIQJ6oYo28D7DCw3Lyx9H4ntyUSEOEJrYKFk9yfJN6EsJg37FUCjDCmPwe0TEVHEHwivJm2WCiQ8NjD8jH5j1EW9CPJlMuOL8VAEOvw44BuYIFgiIlm8NryJywS266KJZUYeqzYuAiD6EWpKs35v3bDz66KPDBhtsUPc5oYzmdegFVTzs8Jo69thj645PeUZyQOxhhehqwhCfI/6awJXi4EXoZqoSV8WUPI/wwxAZYRGvWzzUyImHxfdGHOZJnjSEPG9403HPPProo4GQb8Su2LgX/Xpmbeblvis7di/UxmJz3IZfD9zHW2+9dZ/LUHkWb0ssvl/jkHw8Hw899NC6NhDMEclT92bZMdlxg/U8brafOl4EREAEhjIBPLB5ScPLKv8CcyiPWWMTAREQgV4kIJGuF2e9C8Y8WJtCNroWuorXUl6yfbx3TIiJvX1I4E7FSQzxZskll8xELryefO4xPkdUIleYD/Hk9z4pfMozy6YQjzdy1JUxClmMHTs2OxRxx8SS1LleIEBMobJsyqhqyecpIYCqlRtvvHH2GWG6VkSDfF5eWOJzPPvwFrSQYLsWogziW5yPDrGML6sIhAgR1ocyHJo9hlBBK3CQJ6ggspFTD6OYAR5NZohG5Bozw0uS9Y1AZUKs7xMilXm7pfpK2DNCYGy8WceLzsTL1Lk+/HiJJZYI11xzTbM4Wj6eEFLWnc0lBTJsffhG/f0Ti2xeeOIcxKqpp566T58sZDWveAOFEEaPHl07D1G67H2UB4C1aPd3kUdnLDTGXrLWPiKjD7X1+R692Mq9w/qMK9nCGW9Bs3bGOFjP45YXm04UAREQgSFIgBQXGC/jeCknEwEREAERGJoEJNINzXnt+lHhkWXhfnGS/P4cnA9DyxNkuL4PR+Vtps/dFhdKSPWXjTWhfoTWxoUOfFgq5+Z5VTXLwYdUNhJovDdgKnG9XfuDDz7IwvWwOIQ2LpSQ118S8O+www5hmmmmSR7y8MMPZ6ysumnqIHKX7bnnnjWvvmbZFB2/xhprBPqAXXXVVcmiB977K87/RSEA8qQ1MjwiETLjcN7UeXhOWd42PuccwhvzGFobvnBCf1XDzRvn66+/Hlh3Znn3NaG7Fj4eF35gzIwdKxKPG7H2XqUc26iISqP2+NwL608++WSW2y9lcTh8XqhtHNLqvf388yevujTXtg0d/5/KlVhmXBwjka4sKR0nAiIgAv1HQCJd/7FVyyIgAiLQSQQk0nXSbKgvdQTwMsPjBWFhoKoJIg5Yfi+8ofCKSpkXC+JwVxL8E+6WMkI6qVSKAJnnucNmfLXVVstOb5Q7rpklQ840QvKwRp50iFKIU1iRoOe9deL8X94jKu4nocSE9FK4IC54kTcmxC688/AaMs+2+Fi8zBC7qjQKg1jePfJ6kd8rNrwkyQmGxRVevUdhql9woAJp2WqdKdEPhoh0FF8oMi++5hUsqZKdb8uvP36fJ075SrTcixQXMaMAC7kNMfIhxmHCZfvuvUrLFFEp067PcffYY4/l5gtiLbGmzPKKncSh3ry4MG857+laJLZ67z7mPlVsoszYJNKVoaRjREAERKB/CUik61++al0EREAEOoWARLpOmQn1oyMI+M1vXBDCdzAO5SQ3nBliDaKNGYIU3naIeWXCMglDJXcX1ih3XDPQvEjSqN0333wz8wzCEAZ8Pjl/zTiU03skUa0UzzAz2oEB4h8hwLEHYTNjIcyXkEKKcnAdC6Hsj2IIPn9YXmii92yKc735Yg02RkQavCgR9PI8rlI88IbkPOYnNoRXPP3isEd/nBcTKX5CLsOBsrjYSSpvG2GqsLEiHHHhFsvDSJ8RNxH0WrH+EOm8J11RTjrvfUrf88LZCZlH6MZisZ6QcTxQMdanFaGIWXgv0EZh1EUcJdK1ssp0jgiIgAhUS0AiXbU81ZoIiIAIdCoBiXSdOjPq16AQiL1c8kLEfKGAuHKiz09G4Qi881J5wshNRa63mWaaqS4MMPagyQud43xyitF2Kmw2BujzeSEccp0i855BeR5qcSEDnyPMC1cIR4Ttxrn37Pp4VVEAgmIVnhUCF55GCBFzzDFHsrtxH5jDKaaYorL14wsCIMbiuRQbgqF58MWeWXFuMIRgn6POt8VcP/vss9l448ptCEvMs+U9Q7g5+OCDax58tIPoR3XTvCIivuLnQBeOiMM3qUprhQ2Mga/syu/ivJBeuCoK83zttdcyoZwxLr300n3mKw69zfNma2YReZGOAjFF3r/eww0hm3Dv2BD2qW6MxSHnPmy5yCvWh96nqiuXHZ9/JrGGfK67sm3oOBEQAREQgfYISKRrj5/OFgEREIFuISCRrltmSv0cMAK+UAAht2effXYYNmxY7fpUJfUFJWJRxnu58BleNXFy+/fffz/zlrv77ruzdm+//fYw//zzZ/8f58uKQ/6sI0cddVRWKRYryp9nxzfrPXTaaaeFY445JjsdQQgvrVGjRtU4+JBY++Wdd95ZO8Zfj89TXmgUE8BbyKrj+rF6jyNERUSXOJzzrbfeyqp3WnhxHGpaxaLx4ct4nuGBFhtVWsmLZxbnEfTeePvss0/NU9K347044xBq2ic02CrEch5ehAsvvHBWIZecfWaEgTJvk0wySZ9+xlVBYTpmzJgqMDVs4/PPP8/6a16PsScf3nNU7vVFQvCqs0IuXMCLU/az5US0Dnz66adZiKwJXNyPFB/xFvclrwpsw0G5A/wc+/sg1Qa59hBTMcLJyc/nhVXvycoxe+21V81zjp+9J2+R4M5ziucVVlQIp9E4EVhZVyNHjsz6KhMBERABERh4AhLpBp65rigCIiACg0FAIt1gUNc1O5rAU089lXmumLEJ5mc8m/D4ss2/H4T3xMHDDe8d83hCjKBq7PTTTx8ID73jjjuyXFpecOF38803X61JQvl85U8KWiBYzDDDDAHvMsQV23xzEoUr8Lwxow/ksMI7zQxBy1cdxZPJDO81xALv6UZf8SKzcSA44hlIBVYqRd5444195pHqoiuvvHLt91QfQ5zDEFMQ/si9Rljjgw8+mFXBve+++2rH+4qf9NfnfyP8mAqqiBlvv/12QHw58cQT60I/4+tXsdC8NxLzaIULfNtxxU4T0OwYBE6EFgyOeCYi6hDyy3xS4deHLCJWwQojtJe5pdqnWRy66PO4cQyhkHY9308ELC+0Eva8/fbb17wAyaWGcEy/Uue3y9N7mdIW65r7g3sK8TKu4huHefI5odJ2HJ8jRMGSseFFCTfvJcp44qrBXHuzzTarieTMCRwQQrnHnn/++awwB/+lj9NNN13d0BEUEaERmc2otmdhyHit+WvieYbHrNmECRPqCpBwX2277bbZPUJIM2G+VgGZvuGZN3z48Nr5cV7CvMIXXmjnGrxwkImACIiACHQnAYl03Tlv6rUIiIAINEtAIl2zxHR8TxAgrBHvtDxD3LC8WRwTJ2VHmEKg8oagkMolhgiEJ483RDBCP8sYee4QrHxuM8QuBKtmjFx6VEj1hniyxRZb9BFP7BgEBIQ9G1fskZTKx8Y5sRhDe3iiURHW51TDo8yLU3nncv7WW2+dcUyFFjfDIT7WeyMVFRPx4Y5XXHFFGDt2bK0pBCS8/Lwwy4ep8cRei77YA+ekhEJEz5133jmQz9Asz5urbNVd793ZDj9/LpWLl1122eR9YMchRhMGbobHJsKZGWwR9MrY+uuvX/MGjY9nXbG+Gtnhhx8e8K71XCn+0ozFIfGc6wW0orZYf3jBeYs9N/NC4v1ziPuL0HCZCIiACIhAdxKQSNed86Zei4AIiECzBCTSNUtMx/cMAcQBhKtYWEFEIEQTTyNCFBFaqDYaVymN82ulwOWFsnIs3kCExKaEPWsL4QcvuvjaXlgqO2Hk2UPoiQ1BgLFaaK59Ti4swirxIrTwX4o4ECLsDY8gvJaKxrHhhhtmVTsnn3zyunOZg4033jhXJORg+COebbfddmWH2tRx3gsujxEN+qIGeEHG1VoZP/NZlAuQ6ptUMJ1llllqffTh1VSBJVQyZXjcIVRa5du8PIKEehIqTa7EPGNu8dbMy23XFMDoYDzF8BT1IrcdwjpgLfmcZ3FILv2HSZGITns77rhjVp25aAwIoOSES4nGtrYQPueZZ57aKHxhl7IcuCe4N2LDmzUW6P0x3F+Emcahy4iyeBTaPYWon6oW7T32BrpQSFk2Ok4EREAERKAcAV7qkiuZ7wnkNpWJgAiIgAgMTQIS6YbmvGpUFRIgrA2hiZA3RBQLCSXEEaFhttlm65Pk3y7P5+SPQmwirxMhr/wjN9fyyy+f5XgqMhLck6idnGuEIpLbjgIKhMYSVjp69Ojk6ZyHmMBmHpGCTT7/9f9PSKP9jj4tvvjihRVX33nnnawPn3zySVb5lXPMGBsebHnFHQhdJXyQCp+EE8MQ7yhCAinEANc8Q2ggFxlefbSBIZpwLl5ZhIbGOf8qnP5MwOELMQwJdY1DH+1aMEc8QmBDTEsZawYPN7y4WFOESxLGSK49QqTHjRvXR6gk7Jjrwwxxq0h0on3EYcQbPCDzCnXQN4Qd1hb9ePfdd8M000wTeEtPjjrWVpXFN2IWXI/1iaBIP5hPKpES0sw6Ikehic949PlQUWuL/HqIodwbeGwiVM8555xZ/1dZZZXs/8sYaxOPM0JIWcesJeaDNQmHWABHDEU4ZAzMBf21e4n/53f8bL9DPMOLLW+NEqqKcEv4N3kYYYGnLp6YefcT42KjxksChPq4AIcfN8dw7yB2065MBERABERABERABERABESgcwlIpOvcuen5nrG5fPnll0OzoWU9D04ARGAIEEAEQ+BKeYgNgeFpCCIgAiIgAiIgAiIgAiIgAiLQh4BEOi2KjiTABt28xKgmKLf+jpwmdUoEREAEREAEREAEREAEREAEREAERKAiAhLpKgKpZqolQPgXSd8xiXTVslVrIiACIiACIiACIiACIiACIiACIiACnUdAIl3nzYl69H9FEyTSaSmIgAiIQGcQuPrqq8OIESPk1dwZ06FeiIAIiIAIiIAIiIAIDFECEumG6MR2+7DkSdftM6j+i4AIDBUC/nlM8Zhpp512qAxN4xABERABERABERABERCBjiIgka6jpkOdMQIS6bQWREAERKAzCOh53BnzoF6IgAiIgAiIgAiIgAgMfQIS6Yb+HHflCLUp7MppU6dFQASGIAE9j4fgpGpIIiACXUfgpZdeCvxTMbWumzp1WAREQASaIiCRrilcOnigCGhTOFCkdR0REAERKCag57FWiAiIgAgMPoFx48ZlIt1xxx0X1l133cHvkHogAiIgAiLQLwQk0vULVjXaLgFtCtslqPNFQAREoBoCeh5Xw1GtiIAIiEA7BOaaa67s9N122y3svvvu7TSlc0VABERABDqYgES6Dp6cXu7aE088EcaPH58huPLKK+Xa38uLQWMXAREYVAIS6QYVvy4uAiIgAhkBiXRaCCIgAiLQGwQk0vXGPHflKFdeeeXMrf/WW28NI0aM6MoxqNMiIAIi0O0EJNJ1+wyq/yIgAkOBgES6oTCLGoMIiIAINCYgka4xIx0hAiIgAiIgAj1LQCJdz069Bi4CItBBBCTSddBkqCsiIAIi0I8EJNL1I1w1LQIiIAIiIALdTsCLdPfee688m7t9QtV/ERCBriQgka4rp02dFgEREIGmCUikaxqZThABERABERCB3iHw7rvvhj333DMT5w4++ODeGbhGKgIiIAIdRGCRRRYJ7733nqq7dtCcqCsiIAIi0B8EJNL1B1W1KQIiIAIiIAIiIAIiIAIiIAIVEaCo2uOPPx5WWmmlMO2001bUqpoRAREQARHoNAIS6TptRtQfERABERABERABERABERABERABERABERCBniMgka7nplwDFgEREAEREAEREAEREAEREAEREAEREAER6DQCEuk6bUbUHxEQgMhpdQAAIABJREFUAREQAREQAREQAREQAREQAREQAREQgZ4jIJGu56ZcAxYBERABERABERABERABERABERABERABEeg0AhLpOm1G1B8REAEREAEREAEREAEREAEREAEREAEREIGeIyCRruemXAMWAREQAREQAREQAREQAREQAREQAREQARHoNAIS6TptRtQfERABERABERABERABERABERABERABERCBniMgka7nplwDFgEREAEREAEREAEREAEREAEREAEREAER6DQCEuk6bUbUHxEQAREQAREQAREQAREQAREQAREQAREQgZ4jIJGu56ZcAxYBERABERABERABERABERABERABERABEeg0AhLpOm1G1B8REAEREAEREAEREAEREAEREAEREAEREIGeIyCRruemXAMWAREQAREQAREQAREQAREQAREQAREQARHoNAIS6TptRtQfERABERABERABERABERABERABERABERCBniMgka7nplwDFgEREAEREAEREAEREAEREAEREAEREAER6DQCEuk6bUbUHxEQAREQAREQAREQAREQAREQAREQAREQgZ4jIJGu56ZcAxYBERABERABERABERABERABERABERABEeg0AhLpOm1G1B8REAEREAEREAEREAEREAEREAEREAEREIGeIyCRruemXAMWAREQAREQAREQAREQAREQAREQAREQARHoNAIS6TptRtQfERABERABERABERABERABERABERABERCBniMgka7nplwDFgEREAEREAEREAEREAEREAEREAEREAER6DQCEuk6bUbUHxEQAREQAREQAREQAREQAREQAREQAREQgZ4jIJGu56ZcAxYBERABERABERABERABERABERABERABEeg0AhLpOm1G1B8REAEREAEREAEREAEREAEREAEREAEREIGeIyCRruemXAMWAREQAREQAREQAREQAREQAREQAREQARHoNAIS6TptRtQfERABERABERABERABERABERABERABERCBniMgka7nplwDFgEREAEREAEREAEREAEREAEREAEREAER6DQCEuk6bUbUHxEQAREQAREQAREQAREQAREQAREQAREQgZ4jIJGu56ZcAxYBERABERABERABERABERABERABERABEeg0AhLpOm1G1B8REAEREAEREAEREAEREAEREAEREAEREIGeIyCRruemXAMWAREQAREQAREQAREQAREQAREQAREQARHoNAIS6TptRtQfERABERABERABEQghfPbZZ+HFF18MI0aMCF/4whfERATaJrD77ruHa6+9Npx88slh9dVXb7s9NSACIiACIiACIlAtAYl01fJUayIgAiIgAiJQKYH//ve/4eGHHw4ff/xx4P//97//ZeLN559/nl0H8WaKKaYIw4YNC9NOO232b/jw4WHSSSfN7cc777wTHn300fDPf/4zPPvss+Gll14KU045ZZhhhhkyQWjJJZcMiy++eOE4HnvssfCPf/wjE5FmnHHGsPDCC4fRo0fnikn0/V//+leYffbZwxe/+MXCtt9///0wceLErC9VGmO9//77w6hRo7K255hjjkJOedeG3xtvvBHefvvt8O6774aPPvooTD311OHLX/5y1i7z0Yq9/PLL4cknn8zahNFFF10U7rvvvvDtb387XHzxxS31tZV+6JyhSYC1tdJKK2WD+973vhfOO++8hvfhH/7whzD//POHeeaZZ2hC0ahEQAREQAREoMMISKTrsAlRd0RABERABETAE1hjjTUyka4Z+8pXvhJuueWWMNVUU9Wd9uGHH4ZLLrkknHjiieE///lPYZMIRN/5znf6HPOnP/0pHHnkkck+LbLIIuHnP/95mG+++erOe+GFF8L48eNr17z99tuzjX/KJkyYEL773e9mx1522WVh3LhxzQw991hEwkUXXbTPuL/5zW+GMWPGBPrOdb/0pS/ltkG/d9ttt4bsttlmm7DDDjtk4mUZQzw89thjsznLM8RFREXZ0CXAff6rX/0qE9LGjh1b+UB/97vfhc033zxrl3ubezzPHn/88bDuuuvW1vqPfvSjsM8++1Tep/5qEG9B7qu111478DyU9TYB/q6cc8452XN+tdVWk2dyby8HjV4EOp6ARLqOnyJ1UAREQAREoJcJICK98sorTSO4++67w9xzz107D6+vH/zgB5k3W2x4gL355pt14tNhhx0WNt1007pDf/nLX4Yf//jHDfty6623hgUXXLB23DXXXBP22GOP2s/f//73w+mnn55s56677gpbbrll9hnn7Lrrrg2vV+aA9957L9ugFRkC3SabbBJ23HHHMN100/U5dLPNNgtwLWO09etf/zrz2isyjtl5550bNono0Mi7sWEjOqCjCSAoPfTQQ1kff/Ob34SvfvWrlfb3tttuC9tuu23WZtE9yOdbb7111gdveOI18oKttMMtNsbLiAUWWCA7m/sQwXGSSSZpsTWdNhQI8GKKF0gYL5k22mijoTAsjUEERGCIEpBIN0QnVsMSAREQAREYGgQQ1fBeI3x1sskmy8JcP/300yz0db/99qsN8oc//GF46623wr///e9MjDrooINqn3HsVlttVROY2LjutNNOAS89752F99rf//73LJQTrzIftomXD8eb4Z3CNUaOHBn+9re/hQMOOKAm8iHQ3XDDDWHyySfPDr/uuusyDzRveZ5h/jp4o+27776VTCQhwt6jZsMNNwx4FqUEUPj84he/CF//+tfrrn3GGWeEo446KvvdN77xjbDWWmtlIcKECsOOefLeSYgscMgTNq6//vo6EZLrwglPxDvuuCNceumltevjAbnMMstUwkKNdCYBRHTC0DHW39JLL11pR70gjJfccccdl9s+YjyivBleoQ888EBXeCBxLy600EK1vneLuFjpZKuxOgLHHHNMOO2007Lf8eLHvzQSKhEQARHoNAIS6TptRtQfERABERABEShJYK655sqORAyKvV58E4RpEoKJIQQhDsUhqY0u6b182LD//ve/rwsNff755+vCY/FcWHPNNbNm8azbbrvt6i5Bfw488MA+l33uuefCcsstl/0+75hGfc37nI27hfmSjw/vGgTGK6+8Msv55g1ON998c503IuFSeBgWbfTo/zrrrJN5JmKeg28/Fj2ZQ/rhQ2R9f6+++uosV6Bs6BLAi5P7CusPkc6L5XjJ2lpOEX3kkUcybyO7X7rJ+4i8nT6HnkS6oXvPlB0ZnttHH3104bO7bFs6TgREQAT6m4BEuv4mrPZFQAREQAREoJ8ImEhHuKpt7lOXYoN95plnZh+1InxRKIF8bmY/+9nPAqGfsZ1yyik175z1118/4L2A4RWGp19shPbNPPPMdb/GE9DycRFy95Of/KQyej50mKIX3lOQcNjDDz88XH755bXrwRWB0zzhTj311Cx3HIanUV6YKm2YByChu4ccckifMXjRk+sQEjzLLLPUHUf+MLz9KLZBAv/+rvCKlyZFMDohpJG+9FqIIqGohKRiV111VVhqqaUqW/vW5l577VX6OUABF7znEPRbLeIyWGvKno0Mltx0/X3vVDpRHdIYXsB4U5IjceONN66sVzxjePYWFTeq7GL/1xAvYcy7vOjZXfV11Z4IiIAItEJAIl0r1HSOCIiACIiACHQAAduI4n31l7/8JbdHhHZSJRTbYostwk9/+tOmev/HP/4xILpheJj9+c9/Tgo5Tz31VFhxxRWz47xwSEGE7bffPvv91772tVpIH8KdD8vl89dee63mMVa1SLfyyitn4bxYnneN9zrkOB9mSriUCY/7779/H+9Ag/r000+HFVZYIfuRkFk8F73dc889dfn+8kJ/qfKKOIdYU7YIRVMTG0JAnLzwwguz9UO4Lp5TzB39Jixs3nnnTTaJxyDzTeXZaaaZpvCyrD3COBF28wpzUNmW8F7yhyHe0g+KGyAqF4V9wod54V5AjDZhj7xkrFPCxV9//fWsOjKian8LkHhxMVZyK1IwhRB0wsdZ13h3IXrE4gTzzDEI0ia2EzZNSDViRjMCE9fhfrXqzXPOOWfmDQpDeJh4TLi7CXZ+8uCEOAc/qyZNfsZm1l+ra6rZtZs6nvHb2rHP//rXv2YcCb8vw5J5w+sKFgj3s802W9YUIfO09cwzz2TzSZ5PxKuiyreIlHgS//a3v83EQp4/VOBmbnlpsN566yX7hNcuIhleudw3pDjA65d7lHuE0H08jil6U8ZYhwj+rA36zc+MAY/fk08+Oav2682HDHPPUs2btcl/8UKeaaaZsmcDIfjGp6gf3Kf8HaD/vCDBYMAzmb9JpHJI2SeffJJ5fMINcc0L13hvMx82DnjGxY7gRgVyvEgZJ8ZzDc9u1gP/eu1lQJn1omNEQAQGl4BEusHlr6uLgAiIgAiIQMsETKRjE/XEE0/ktkPuOiqlmpGLCk+usp4M5557bsB7DkNs87nw/EXZ1HtRx7zVbrrppkB1SOyEE06oywfEphFPMTM2jYsttlj2Y9Uina+Ui8AUV7+1PniPQJ8XD29EhCDs4IMPzvL8pcyH/i677LJ1obRs2ldfffWaUDmY+ZGYH7y3ENzyDM9BhARvbNIZF4ZI53Pnxe2wuWYjnrd24IFwlRKMrC0E4iOOOCIpZnjvSMSQ4cOHZ96OhAfHlucB2vIN6E5EnCNn4XnnnVcLdU61i2Drcx0iMlBtsoxxnyO4x8K2nYsIsueee+ZWH+Z8C1/luF122aXusvDhXk9ZXth2fGyra6rM+Bsd472lio6FA/c+LytS7P3zEibk7zv77LPDWWed1YdtUQEORDmeE0VezohKiEe+UI2/vxgHYt0GG2yQnFfCOOlDniEo4snbqA9xpV+fdoC2yTNqLzj8tWDJ/ZbXB4RNxsf6yTPuYY6ZddZZ+xxCtWNbp1wDQZ7fnXTSSX2eWyYmmuCHyIpXtqUeaLQmGCNe0N7DutGa0+ciIAIi0B8EJNL1B1W1KQIiIAIiIAIDQMCHdOH9kWd40FDkwBvCGNVC8Zqi0ATCgS8i4Y/FA4mk81hKtPHH+jxq5LVCNPEJ6xEL+XfjjTdmp+ElYgIgP/vQ2qpFOh9iWsTLV7H1Ybs+J12R4HPnnXfWBDw8NvC6MyN3IOMyIzcdxScG2nxYMdfGU2r8+PGZxw599BtbcvMtvPDCtS76Crz8knDmvByHeIeZAIDAZIU3rDG8+BAyzNgok5/vwQcfrCvqkcqhhsDnKxgjqCKU5Rn3gFV4rJI3YgAiI+JBbF4Y47NY3E3layzqW54g70Osy4wNjzp4eUNwTVV/5hhCHhGqiqydNVWmz42OQYy64IILGh1W+xyx3Lyr/EkWZs7vEKh5kZDHJc+LecKECaXDlWMh33suNxpMkWcz7fAiwYRZ31a8LhHlvDebF9cb9YHP42eEnRMLv6wxKu/iDWje3RyLBzbP19hYc3gzYnje4QlbVGEbb0HzbMQ7tdmK2Dy7G1XkLsNDx4iACIhAOwQk0rVDT+eKgAiIgAiIwCASKCvS0UUvMOV1mVDU448/PhNJvBFWZd5WjXJlec8mC+P03hCEjw4bNqyuUiybLhNbCJVDNMSqFunMkw6Bkg1syu69994sJNA25d6DCLHJcuQVJdLffffdw7XXXps1j9cinjhmjMmKfOy4445h7733HpQVRDVe84CDB3NknixsbglFRkDEqPTrxQ/v7cjniLiEosVGyCSbZBMJEMi8WPzqq69mG28zPJjw7MPDE880xE2fIxBBCxHPLK7i6a9Pn/nHfOJhhsViSFXg43vrW9/6VrZ28QhFgMULEC8sLM5RSGgpn02cOLHO4xJRDCEF71S8keABF7wSqQLrjXO5phdj8LYbN25cIIwYQZxwP298HueJ5H41VngTIWQT/o2tuuqqteqYedzaWVNVzAXPKNY0oZx+vISMwtD+wRKxBzEuFS7qq+z6frH28LxDlMWTywzP2dgr2b/Y4DiKguARxj3GswX+CEoY94CvpBsL+XYd1sTyyy+f/eifG3j+xmsCsd2LTawlnjfcEzzfec76sfMihxBWs5SHJ4VECIudf/75szBT7nlbcynB86WXXsrWoL+/Le0Bv/MvQ/iZZ1A8H7wUIhdobIijCKj0xVcOjz1V8a7Eu5NwW/sbtsQSS2Qvp2w9IPZzn/GCiXnLC72tYo2qDREQAREoQ0AiXRlKOkYEREAEREAEOpCA91pLbRTjLiO6EAbIRrwoBCje9CE22PFsdkaOHJlLw4t0Jr75qpJWtdKLVT5k7IMPPqgJMVWLdJaTjg0eQhwiEuPiHxs48nh5oQPxilBdy8dF380rjtx0lqfPw/Ahd2yMEQPJQYXF4cB4GCKMDrTFm2dEJsslaH3B02WVVVapdQ2xhg2xGYKDeY7BB8+3eHPrw5w5jzZ9/jofVpjy1IrD/gg3xtvPLOWtBHOEZjvO5xgktDAO66uCvc/56D0vUywJ+95nn32Sl/X3M7m7yuT6oiFfuZKfU5WAEa8Q0czKhP4iIiFkYQgiVjQl1fkq1lQVc0EbhHiamNWoqE7qmimPwj322CMTuchphwjoQ5ZjLzQ8xFgTZqxzL07xe/9MpAq2Dwf1n1kb8T2KRyZeqBj3IuHL3ij44V8OEO4KC2/0yURZ8t3x8sTMi3Tc34j08bMq9t7kmj5k1Yu2CJyI7LGRc7JICKYCOC92vHFvI3ybBzLCoeW5i0U6O88/rxD9yoaYV7Um1Y4IiIAINENAIl0ztHSsCIiACIiACHQQAb+pb7aCIR48bGbZUJKHyot2CB1s6kyc8tdJVWT1SPyxeDFRFdJ7TLCxw+snDqfC8wyvK4QzwqGwVGEJ+nnllVdmycDNw4j/kmAc7xFyTbGh9mGQ1j/vEdhoGvG6wvPLJ8zHi9Byp+E5Qggm3id45uCxhGjlc6HFXnRshH3upnhj3KhPVX1OjisKB2DMNWHJqTxMfvOLt5flluM81gHhw2bMCQKtN0KZLTQNTyILW7NjvBjiveTwsGPNxKIQxS38fPgCHdZm7G3nxaOiPILtsEUMQaDA8FJijcDC5xmjWAjzjdjlPZbsuqxhigGYIZL484v6h3hk4eNFIb1eNCnyBPUsCdfGGhWcqWJNtTMH/lwf3p8nDhVdyz/DOC6+j7nfEQER51JhmgixCNS2HliTccGK888/v1bAJ/aojXPrpfLOUQ2a5xyW8mKLQ2bxEMMbkrB08/rDA/OKK67IKnfzTPbmRbq8vJP+hQrnIoD7wg3+/sYD2Yf527WoZoz3LMb6p8CGN7+2+T33Gs8FX+zB1jXPBl4iTT311H2ml+eP5eWDvYm4Va05tSMCIiACVRKQSFclTbUlAiIgAiIgAgNIwG8mY2+OZrrBZouE3D6siJBNCyPy1ynKoRbnCLMQKjaC5j3kxRzat7A0QpAQuOgL18NSRSriHGapcXItK1ThPy8S6bg+AgvhVhyXSmKOkAiXMoYnDaKU9y7z+ccaVeQtc41Wj2GeTQArCgElNJP8c1hqk+2r5cYeZLFnFe34oiJejKV9RCyEBRjZNf34Uhtr1iIhzGbkr8IjLzYEYXIdUhmyPyo5esHFX5v1BF/CGamCWVRZlgqvo0ePrp2OADnllFOWmmIvpqa8Iq0RQjQp3ILleYL6C/owdV9AJdWpqtZUqQE3OMjnTOS+RtBqxnwagTg82dpBSMYzFHHLF6BBwCNc3zxy8fiiAmxszIOFzOIthkeZmfeMZG4pRhKbrxAdh8tyLF67iG9xPjpEeUJQEZFZk3FqA7uOF+k4lud2yrwQRyEOxFy7vr/f7SVM3Abeyz5UF+9Zf4/6/IBwxVOOiqze+JvBs4PxpgRwjuXlCCI5Zi+KmlkTOlYEREAEBpKARLqBpK1riYAIiIAIiECTBNi0vP3221moUZz3yIehFhVCKHtJL8r48EO/abU8c6k2Y6HhySefzIQJ7xmCh5TlIYvDGfHWYgNpOelSuc7y8jVZf/CcQYDygod95sWMuP9UWUWIKBJSfAGMPKZsgimOEOeIss0hYbZYf4VelplrPL3wCsRSBRmsDfJe2eY8JZjymc+N5T0DDz300Jq4kPI2isNp8/rN5hpmcagex/uwQsQGy/VXhkGVx3z00UdZuGJR0QrWBZ6FrLPUGouT3DdzP3uhBI+61NpnvHiEEcpu/+/DIVM8vAdsoyrEVa2pKubFi+HN3mfkm/NFUGLvzUb9e/311wPCoFnKw5TP8GQkfBs77LDDsvvQzM8Ted94DsbmvXLzQnoRsQm1TVVltfZ4FhMqG3vBPvbYY5nnHVYkdHoRDc8+1glG3j3WpVle+HYs5scepL7YT54I32hO+Ny/oMkLiS3Tjo4RAREQgYEgIJFuICjrGiIgAiIgAiLQAgG/0UltUMzDLa/iY7OX9JtyhDIL2fKedKnk3nYd8uL5cCcTGrynUbxB8hUZrYCBiXh+0+fHQi4yNtN4GuHFYv9t5CVlnl8InohOCEmvvPJKrWmuj9Di803565K/yXJLsQFFiEOYxINw+umnz8RFxKI4tM3a8B4yedUMm52zVo73Se3zPIVo14dxEh5rob52TTxY2MCbtw482bTHQkVqU0xYWsrDyNqmXwgX3hsnHqsXbOPiFq1wafcc1gIh3oyNKpF+bVnb8EK05p715iujNns/+7Biy/mYGgvec3jMYmXCXb0I28iTrqo11e4ccL4X032+yzJtEwLqc681I5bSPh7NCEJmeeKUf+7Fc+EFbnJgWshx3nrh97EHmj8WQZw1SbinhXzGLOKQWi8CwsOqe8fn+dyivpI1OeJ4KWIWF6aw38dhuU888UTdveG9dYv+9jSa27zQ+kbn6XMREAERGAwCEukGg7quKQIiIAIiIAIlCNx8882ZdxcW54QirGqeeebJPkvl8inRfJ9D8LLBiwNDoLH/994MJ598cpYDKWXeg8Vv7PCQI+wLY0wLL7xw7XSSsC+99NI1oYewL0L2sLyw1VbGxjlWtdGqu+IBRZieeRdZu3jC+cTv9vs77rijVhHTb0jL9seLlUUVZsu21+pxFFZgHjEESUS02OJw1Dgvlx2PBxm5+zA8eig2QCifhU4TDugrtNp5Prm//Y5NPTnVENyKPBrteH9/5F2nVUZVnIfwhmhHuDc5/MxS91A7Ih1FIMgriRUVhPAhluTxslxgeWP1ORgb5aSrck21y96H6abytRW1/9prr4Ull1yydkizaQTI7+ifj6kcnuQfZK1btVG8Ucm9ZuaLJeQ9A+N8cGVzGPJyAwGOe4f70gT22BvPe7r6FzYxOx9GiohvuS7j/uWJxz4EO5UCwHvApQqilF0rvqBRHHpftg0dJwIiIAIDRUAi3UCR1nVEQAREQAREoEkCPuSIDQyhppanipxI5nGWl7eIy5GbiKT2VBi1MNJUNyi8QDVPq5J39NFHhw022CA71FfhLEpM78U873njxT88jEaNGlXXBXIu4T0SW5yrqUl8fQ43kY4PvIcMmzY2lz5/U8pzyOe6SlXxbNS/2HsM8Wbs2LG5pzF3eIuRHy/Pu6/RNVOfx9UjU0VHYg8XvCpT6yeudImYR4ieWd4YYW25BzmWBPJWMCTuM2HT9BFvGKuUyzG+cmuRkNAKo7LnMEd4WHJfxhVyrQ0EdTzorDgL4YVUm/QWex/meR6l+nXZZZdl9yiGYM89FofGI0ivsMIKWRgilgolj9v2xQkarfcq11RZ9nnHeY/XZgtHxOu52eIucfgmlUnJ/eYtZhUXyPFedkUejD4NQVwwBRGcNcQ9M8cccyRRec9pDuDZbwVkfGGfvFDymFXs7e2FMULW7YWT74z31k15F/sUBXFhimbWiRf7ivI2NtOmjhUBERCB/iIgka6/yKpdERABERABEaiAgPdUIJSQ5NyEdeKhs9FGG2VXSFVBtUt7gQxPGl+R046hKiqeHAglZlTZs2qTPkk5n1OxM66eSpgoHmhm/hg8rfC4yjsXgZBqeyYgWBtFXkGtoPUs47AqwsUIr/R9iEM88RJjDjCfs69sXxBpyCNohrCEt1Ic+sjnXIu5Nm+bZsWCoj7F3kKpzS+ej3hAmj311FN1CfJ9+/Gx9llRmBzH+BC0PI8hX/0RkdV7PXohMS8vV9m5afU4wkcJI8VijyhrE09Fy9XF71Jhe4RM42FqQnEzAjVFMRB77VzEEPpiQh3eU/C1Ii30oYyHmQ8bbXR81Wuq1fngvLhydDNhkjwL/UuEohycqT7G8xhz434m15t/IRC/ZPEejzzjCYdNmb9/vEDmvdgshUBcCAeBDa9l8/CMw8U9wzxPba7pKzY/+OCDYZZZZql1lVx75hWNSE34tE8FED8PvSeeNYI4zH2Oce+ncn2WWSukKUC8xTohNL5Mn3WMCIhA7xKQSNe7c6+Ri4AIiIAIdAGBeMNJzrfx48dngppVwcwLRWR4PpyInxHj2OiwEaUgBTmKENG8OHXQQQfVwjoNkfdCwzuFXEl497Exoy8k8TeLN0E+FxbHzTnnnH3Ie68o+xBhb80116xslvymNiU04p2I96AJY1zYb369SNdK1Uja8wnj+RkPOQQVcq/h/UKYGQKp58lGm3mKqxq2A8Z769AOawihhzBTig9QzdXMV/pNXTMuemDHEIKJ91ae+XBKhEryYjFHVMSFxQUXXBAuvfTS2umIG5ZTjV/Gea+azR/WDj8714ea8jsThPCeo+gAIc6W25HPiwpc+Nxy8EBYWGeddcIMM8wQyPfI+uO/hKpON910dd333nR8gEBKERZEJ+7PWACPhRdEI4RrwpzNuCfxBLN1So5IM/q3+OKL1/WhyjXVztzEQhtjhSUiPYaHMvc/6yzOs8jnPgdn7KFWpl8UrvGVspkvxDo8mhFL44qrcZinr2Bd9DJgk002qeWYs3yQ9C/2cOPvBf1BIOOZf8MNN2QvTcyzk3MQ5Mn/Zob3qlV+4+k4AAAgAElEQVRKjkPz8R5lTfkK2ry8iL2hyR1KRWUz2iPEmr8fvBThuWcVV1lPvHgaPnx4HWKf67CdlzbxSyReyCAA0hdyR3JtBEvGkVd4pczc6xgREAERqIKARLoqKKoNERABERABEehHAmyU8azJs6IKhOS6wlMj3hjmteVz0fljqBS4xhprNBwlG7prr722LsTK56tioxp7dVij3muC37UT3pTqqN9851X4Y+OKMGJCHRtoNm94JflCBa16blFcAKHVb5CLoLJ5Zf5jQaThRDQ4AEES4SBV3MCfyvgRCFPefv447/3D7/PCLv05iCkIurGAxLVSQgainvdywoNs0UUXrTVZ5O3XLq+8871wa8ek+s9nsCQP2Pzzz59s7tFHHy3lKYT3EgKNN4QTRDREwjxjTrwA7YsN+AT9ZVnFecaqXlNl+5E6zgtdRe0gRMbz4VkgfiJ2NmPvvfdeWHbZZQvvcZ7Jvhoxz1fEWAxR1wSwopcBvqJuXGTHv1Shzbw1yWcUf+Dviw+RjgVw1u6IESOy/iGg+/uTzxD2U2G13tO0iGHqxRDHey/d3XbbLfDCoBXjWYFI2Oh5F78IaOVaOkcEREAE2iUgka5dgjpfBERABERABAaAgC/K4C9XlCPOjmPDhUcCXnl5xgYeLw82MnlVUjmfipx5AhPhm2eeeWYYOXJk3WUsbK6RsBULgXled63i9p50eJN4gce3+eKLL2YCFuNEdCTkDSa+f+0U68DzDI9GC+PKGw8beTavcWhxq+OPzyNEkSqq5s0Sf47QQAhzXk4rf3wcclnWCxLGCBJFLPAKwyvPh9LZtX3eqziEuSpORe0Q3ohw4ENJU8cjtiBWN5pL7hXyd+WJ6ogtiDhWNCa+FkImHm3+fM5B1KOfiL18Fos//t4oy42cZpYX086pck2V7UfqOOaFtcvzKM94XiFqxtWY8fAiNBNr9UUBAij3lhdFrR8UpeG+9jkZfUiurxBbVBDFF07xOUS5Ds8qntVFL2dYF4Rhp6rHxlVq8xjyfCTvZNG6bvSSCU/r9dZbL/l3x+fv45nJ3LRq/P3iWZOaE2uT9YLnoUwEREAEBpOARLrBpK9ri4AIiIAIiEATBAh1Q6wjzBWPNN76s8Fp5OXEJfC0QQjBcwQRCo8uRDM8k/Akwbsr3qymusamjxBX2iKsikT+iCds8gkdyjO80QjpjMOZ4uMJ92QTRREBQgOrNEK48F5hc4wHV5GRyB8xBC5+A8rvXn755UzM9Inbm+2nFYWAC3OJ981MM80UZp555ixUkevmeVw1e62i4ykoQB8QIhFz8Yphnuabb75sTvME21Sb5C7E84j1QLhsmfVka5NiB3iSIRgSKso6weOSyr94MuWF+rIOzSsST8zBMu5JRGU4MgbuLdYHc4hnZtG9EfeZ+wpvVO4FChFMPfXUGQvWBV5ezFGRUT2Ue+jpp5/OPBqZS0I7sffffz/gXcvv/fxwLfqONxW/Z975L+f5f/yOfwjxeYU+qlxT7c4nDMhFxpzwzJtmmmmyeRkzZkzG0gol+OsQNk2Y8vTTT5+FyZapNJzqJ9fjeYEnKv1AWMUbGREIzpYvlPnkucz9b8Z9RD9YO3nPQZ4hiIg8O7baaqu6oiq0Q7gpfy94vuDxidEHnmcI8Pz9YG2lDO9W7n8zXhjQHvnuuC5rikIP/Gv0TKcNxsK9yt8O2qAfrEFC7IteAhB+TRg8f3eoMMx91Y7hvYsQjojJ847nCh6M5IOkuATjkomACIjAYBOQSDfYM6Dri4AIiIAIiIAIiIAIiIAI9BwBhDwqA1vV7k4BgJDrK08PRr7HTmGhfoiACIjAQBOQSDfQxHU9ERABERABERABERABERABEehQAuQX9KHMEuk6dKLULREQgSFJQCLdkJxWDUoEREAEREAEREAEREAEREAEmidArsjFFlusdqIvMtJ8azpDBERABESgGQIS6ZqhpWNFQAREQAREQAREQAREQAREYAgTIM8dhTXMnn322dI5JocwFg1NBERABAaEgES6AcGsi4iACIiACIiACIiACIiACIhA5xP4+OOP64ooUGQhVWSj80eiHoqACIhA9xGQSNd9c6Yei4AIiIAIiIAIiIAIiIAIiEC/EPj888/rqlo/9dRTYaqppuqXa6lRERABERCBegIS6bQiREAEREAEREAEREAEREAEREAEagS23HLLcNddd4XZZ5893HfffWHSSScVHREQAREQgQEgIJFuACDrEiIgAiIgAiIgAiIgAiIgAiLQLQTefffd8OCDD4YxY8aEGWecsVu6rX6KgAiIQNcTkEjX9VOoAYiACIiACIiACIiACIiACIiACIiACIiACHQ7AYl03T6D6r8IiIAIiIAIiIAIiIAIiIAIiIAIiIAIiEDXE5BI1/VTqAGIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAh0OwGJdN0+g+q/CIiACIiACIiACIiACIiACIiACIiACIhA1xOQSNf1U6gBiIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIdDsBiXTdPoPqvwiIgAiIgAiIgAgMQQITJ04ML7zwQlhggQXClFNOOQRHqCGJgAiIQHcR4Jn88ccfh1GjRoVJJ520uzqv3opAlxCQSNclE6VuioAIiIAIiIAIiEAvEHj00UfDQQcdFPgvttNOO4W99tqrF4auMYqACIhAxxJ47rnnwnLLLZf170tf+lLYdttts+fzF77whY7tszomAt1IQCJdN86a+iwCIiACIiACIiACQ5DAL37xi7D//vvXjWzdddcNxx133BAcrYYkAkObwHXXXRcefvjh8Nlnn4VPPvkkfPDBB+Gjjz4KU001VTjwwAPD7LPPPrQB/N/oHnrooXDLLbdkHmhwgMGHH34YJplkkrDllluGsWPHFnL4z3/+Ey699NLw0ksvhf/9739ZO7DkvyNHjsyemVNMMUW/s+T648aNq7vO1772tXDJJZeE6aabrt+vrwuIQK8QkEjXKzOtcYqACIhAhxDgS+XRRx8dXnzxxbDrrruGRRZZpEN6pm6IwOAQ+O9//xvuu+++zDNhscUWyzZuvWh33XVXtmE1Gz9+fODfd7/73TBs2LBeRKIxi0DXEnjllVfCN7/5zdz+77nnnmGXXXbp2vE10/Fvf/vb4V//+lfyFBhdeeWVhc3dcMMNmcdannF+Eetm+tro2EceeST85je/CZdddll48803s8MZ34UXXiiPukbw9LkIlCQgka4kKB0mAiIgAiJQDYH99tsv+3KHfetb3wqXX355NQ2rFREYQAJ4h/zqV78KK620UkMviKJu4SGx+uqrh3/84x/ZYXgl0G6vCXXkn+N5AA8ML5ttttlmAGdUlxKB/08Ab6czzjgjTD311GHDDTcM00wzzYDj6YQ+tDNovMW4p03Iidv62c9+FjbbbLN2LtE15+64447hxhtvTPb3+9//fjj99NMLx/LXv/41rLbaarnH3HrrrWHBBRccUB7//ve/w1prrRUQYzG8+bbbbrsB7YMuJgJDlYBEuqE6sxqXCIiACHQggT//+c/Zlzpvzz//vJIPd+BcqUvFBNZee+1ACBOGV8FXv/rVlpCde+65gc2qt2uvvTYsvvjiLbXXrScdc8wx4bTTTsu6L/G+W2dx6PQbz1bEOWydddYJxx9//IAPrhP60O6gP/3008yDjJcOFBk4+OCDw+9+97us2RNPPDGsueaa7V6ia87/5z//mYWqwuLXv/51OOGEE7K+r7/++oHnXyN79913w+uvv56dTw44vNfM/vCHP2RhrwNt99xzT9h0002zy+IJfv/99yvsdaAnQdcbkgQk0g3JadWgREAERKDzCPDllDfBf/vb3+o6x5e8ueaaq/M6rB6JQAGBH/zgB7XCBuRRW3rppVvi9ctf/jL8+Mc/rjv39ttvD/PPP39L7XXjSeSrGj16dM2L7pprrglLLLFENw5FfR4iBBCSNt9882w0rEXW5EBbJ/Sh6jHvtttugTx1GJ6Kq6yyStWX6Ir2CE/de++9s76yzg499NCm+73QQgvVnpkPPvhgmGWWWZpuo4oT1lhjjSzvIEbuUHKIykRABNojIJGuPX46WwREQAREoCSB2267LasEFtvZZ5+dhQzKRKCbCGyyySbh97//fdbldkQ6wjtXXnnlWr4iPEvwMOkle/zxx2ub9RlnnDHzUMTrRiYCg0XAe30PlkjXCX2omr8P+zz//PPD8ssvX/UluqI9ikAccMABWV8JEY2L5ZQZhBfpCIcdrMINF198cVaNGyN1w8knn1ym+zpGBESggIBEOi0PERABERCBfieApwxCHHm3qObGF7of/ehH2XV5s7777rv3ex867QKff/55lstlsskmC7POOuugdY9+DHb+s3b7QOEFCpEg8Ew77bQDwhLBGeEZu+qqq8JSSy3V8nXp/5/+9Kdsk9VOIRWq/ZFDq9vMh/xutNFG4cgjj2x7CG+99VZ47733wogRI7J7rFnrBJad8oxoll1/HN/uM6LZPv3973/PxHOsTGL/Ztsvc3x/9KHddc08kGvui1/8Ypkh9DnGPzfbebnR0sWjk9p9RrTTh4suuij85Cc/yZqggNYee+zRdHM+AuHJJ59seU6avnB0wnPPPReWW2657LeEvPLSZbC/U7Q7Jp0vAoNNQCLdYM+Ari8CIiACPUDAe9GRf+t73/teLdn+sssuG3gT28jYGJCjh/DY1157LUtGzT+SF5N8et99961rgs/4IjzHHHOE9dZbr9Azh43HqaeeGh577LGsna985Su1ts4555xAZTXyEnEdcuwQsouowpdRjuUL6pgxYxoNIfv85ptvziq5EZ5iSfK//OUvh2OPPXZAqrMxVgoTkMOGKm0Ip4yB5NU//OEPw/TTT99nHJxz9913hw8//DCsuOKKuaIHx11//fXZnNDWlFNOmWTSSh/ihhC2mBvywVluOI4hTw8iTyo/D2IxuYDYqBKumlcxlA3Pb3/722xeF1hggbpLkxfojTfeyDZY5knHOvvGN74RpphiitLV7ej/+++/n/WFBPGEg8NrzjnnLLWOOIhzEAjvvffebD0h+iJUUnyCPEFURc0zQunIATfPPPNkvPBce/bZZ8MDDzyQtTXDDDNkYxoIL1fuOSsg004yeUQNErAbC9s0Uqxm4403LnwGtMNysJ8RVaxrWPFMYE2w+WdN2Eab+x6vLnKLkROLCt0777xzH1GAdXzYYYcF5oEQbi9ck3sUbx97diN8fec738ldn60+I6pY14yTZ4AVLuE+oHIlYi/3+EB4eVbVh3bWtU0OYjfj/8tf/pL93ePvFn+zvv71r2cC07zzzlv6mUX1Zqo4Y+2+3Ch9UXdgO88ImuF7yBVXXJGxePrpp7O1Tj5S1jPfa4rWtO8vzwzuFYx7hfupWfMiHc9u8tSVNdbFo48+ms3FCy+8EBAs+bvG/cnfBNIwlF3n/C3zawA2/B2SiYAItE5AIl3r7HSmCIiACIhASQIIQAhbvGVFUMHbZ7HFFstENn7HZ3lfCNkg/PSnP82+NBYZYhMbKDM2WOT2wvhCjLiUZxxnGzKftJ5Ez4iIZoh1G2ywQU1c8+0hDjDOPEPcIWk2RQHyjKq348aNK0m1+cMQzxBEENxSxlwgliDyeLvzzjvDVlttlf2K0C9EVY6NjRw7CJBYntjSah/8tXhzjwcmm4yUsUG45ZZb+ngo+nGwKYpzwVlbiHNcg3b++Mc/1tZVowp7vi/wIfG8hQH5z2666aaaJ2nc/7JJxN95553M+wKRMs+22GKLLKTK3xd2rN1//IzISBLzFE821Yccckjzi62JMxgznLFWvGsQqc4777xw+OGH514VVggKKWuHZSc8I9pd18YEocEqNVItcvjw4dnLg6uvvroPttT9jfi/yy67ZMfyLETw43cnnXRSdj/F9wcvRVJeju08I9pd19tvv3327Ghk3N88HwjZbLVoTN41qupDO+va+sbfVbzf4vnzfWeN8CKsjPGiy/7+DGSBnHafEYwNAZjnOQJqnu20007Zc7mR9y75+I466qismX322Sf370ERUy/S8Rwq472GOMe1eV7mVd3lmrxsQ4Qta3idIlhi3PNlX1qWbV/HiUCvEZBI12szrvGKgAiIwAATwMuHEDbM517xIhpffnl7G5t5ybFRiI0Nkv+SifDhQwX9ZqCRt56v1MmbcEQLDOEAAaGMsWnD2yQVBsSbZr7E+nFw/KhRo+qEkVgUKnPdssfg/YCXmWc2fvz4wEYOD0VvbKLmnnvu2q+o2IY4aQYjvuT7N/f87JNfE8K4wgor1LXbTh+sITZIvqodv8erAy80zxeRAOHUG54be+21V/YrPOlOOeWUJD6f64f1S8gkhnDBGi5rzPETTzzR5/ADDzwwXHLJJbnN4NlQZGw4GZ9tijh21VVXDTPPPHPmDeU5IHAj1nmLPR8ajae/N11eWIHxggsu2KhLdZ/j1Wj3rH2A0PzMM8/UCeqptttl2QnPiHbXNczwXPP3/A477JBt5vOMKt0///nP6z4mv6gJpXif8SzMeyHAiannfjvPiCrWtQn0ZRcgQotVgS17TqPjquhDu+uaPvL3d+zYsbXu8veJvxl4k/NywP8twUN84YUXbjS0jJX9venv54rvTDvPCNphvFtvvXXD8XEAL8K4f4qMvz0UWcD4e2AvCUtdIIQQr/VGfzNoFw9Y/v7BPTb+VplnP5/xQtFezJXpk/++1csFQcqw0jEiUIaARLoylHSMCIiACIhAywSoXMZmDCOE0EJJCS/lDTzG/1P5NTYfGsNnJOtHXFl00UWzDaB/e3vWWWfVcghxbCwaITQR+hqbT1rPZ94rIO+LOSGAlvDaKrRxLl+86V9sPv8Mn+HdxBd+3rZTNdDno0mJWy3DdyeymbRNN54fXMc25Yg9CJX2JT0WuNjAE77qvbb42bzECJH0Fd3YwOOZFb/Zb6cPNhSf04iNBUKchRjhGec9LuOwG7y0LEF3kcdanmhEeCrrbOLEiXUh2qwH+sLGic0x3gp4hrI+U+sBrwe8JgmdmnzyybNNr4lMecKeXwOE7PrwKB82Rh/YYJGYHKM9wj+95yP9j70lORaRm7mbbbbZsg2kec9w3xV5qbW7Pr1HCKIXeSvLGl643oOV/iMWE8pMiKUPP2MjzIa4Spad8Ixod13Dg3sfcTplhE3zD8HavMxSLz54dvIsjw1xB08rKhbjAWuW8tZp5xlRxbrmXuGFz1NPPVUTk3gJgAcx9zb/eB5yj1NNE8+pqqtqVtGHdp8R9nfKniPck4g7lj+V0Ej+BlhVT9bHBRdc0PC29S/E4hdrDU9u8YB2nxGEeyOcmpcp3cCTlGfNVFNNlb1oY12bh12R164NgeJAJnI3K4jRBoLbfPPNVyNSRqTzIbacSNQA30P4e0d6gyOOOCL7+4Y160FNXmGLEjj66KPrXuq1OG06TQR6moBEup6efg1eBERABPqXAB495GnB8KzwAgrCHQIelto888XY5wPjCy1fir35qmKIHH5DHm/YENOoLBebz4eFkIGwwxdv7LrrrqvbVPK7OHSWL9jk68EI9dpzzz3rLsFmZplllqkJYOTHIpzJDKGGL8kmkLWTkytvNmPvs9jrgU0nX7IZL4aQiqDqjfngbTmCnBlzAnPm2LwqEH8QjYyhHVtFH8hHSK41szhcihx7VJcziz2nmCfmC8O7DC+zlOGpZxsuQpwRhWPz3nbkaULYatUI6TYvUAQN1mCeIQ4gkFj/vFiat6YQ2BDazF566aU+YdWsXcJBzTsSMcbWKWFPCCr9YYgePgdkM/mMYIE4bDkJvRes9dUL/bH4XAXLTnhGVLGuJ0yY0Kf4Cc/D448/PvOewnxagBTrlIco57L5RwTAeFaYp2cs0rX7jKhyXRP2b3lOeeZY/rD+uAfy2my1D1Ws65hlKmVE/IKL9YEQW2RepCvrfdcO83afEVzbC2r8nArT9akejjnmmIYe+LzEIgwc46WCfRcqO9b4+1EZkc57MaZeUvn5pLAXYbhlje81vHjC8Fos63VYtn0dJwK9RkAiXa/NuMYrAiIgAgNIwG/aEBbYoCFaEWLJJsA8sxB2ePPvjYT6PuwNbyXEPI61HFt8AScHGp5IhNTGiZPxWDNPALwhCL3yue9IluzzrhAKgmeEmRcB+V0q75z3hEMgOvnkk+vG4d9eI0awkcF7ypvlKMPDjTDIZjyJykyn96qAI2FpGAIJ3jF42PmQV8RM7yFo1yCvHh4xPsySObKf83LBcX4VffCCS54nnIU1IcgwF35N+DxAKXHLxunDzVIbslhYIlcdlVlbNe6JxRdfPDs9JZD6dmMx5cYbbwyjR4/uc2k2fniTYrFXhK8ayedsEH2oMr9j04e4jJXx7mt17PF93gzLWJSNw7TpE9505mkHDx++VwXLTnhGVLGuSYIfh6fHIrcXblLePzw3WI9mCKh413mPWnsm86wgNNtXI273GVHluuZZj0cQ5tM0tLrOWzmv1T5Usa55OWF/C7n/uddSuS296Bp7s6fGvMYaa9S87wZCpGv3GcF3DF6g2Eu01LOScfr0HfELwxQHPJUt3UIrL+bi52YZkY770V6y8V2D7zvkofR/u3gRhuchf+dnmmmm0svWhxPH36NKN6IDRUAEagQk0mkxiIAIiIAIVE4Azyw2OEU5jeKLssHyG7b4i68/Hq+8pZdeOvuCueSSS+YWnYg3bQh6nGPmN0H8jtAd8/jgZ/85mxETPXxfvHdX7C3IcT4EE08lH9rq28GjLvY+q2pi/Ft7+gMzPOUIX/IhPFyPEBjClvL68uqrr2beavF5nFuUbLqKPvgw1KICA4QCpSrL4rlAP2xtxaGPxttvPFMVCBErvTCGwJFXybbMHPrcT2wIEW3zjFA4Kg2b5VX18+JwvHbJnWheqYglVKmNC4HE4Y/tjjFvPFQE9Yn3m/Gk8wI54Yj8nDJCgBGK4mTuVbDshGdEFeuaZx8CihlCfqqyL89UXrJQuTUOZ/epDVjHPA/iFxKIC4Q0450aiwDtPiOqXNc+7BYvYx+mW+aeruKYVvtQxbr26SiKcrr6FydlPKgI/7cCNQMh0rX7jCDs2ReduuOOO+rCTG2evYdgmVx7eNtRWAVrRaSLn89lRDqKnKS8x3n+Msd8f+HFTCqvbqP17D3pSCnRTO7WRm3rcxHoRQIS6Xpx1jVmERABEehnAk8++WRyg1d02VhA41g8Avjif9ttt+WeioccoRl5ybv922PvRcZmkY29vSEn0bOFN9nF/NtuxC2fB8yO8flu6AuChzerbMvv8ja+/TwddW/5866FWMMXbcSbRpXp4jAn2mwU4uM9DVrpgw8J5fxmxBy7nhczCMdhbaXM5zpMVdz1nm+cX2aDVDTHvkJokdhEG3j2IRpgqfVm1/FhmLHw54VlRGuryBv30eeKy8vpWMXa9dfxeSsbte1FjCLPyLx2qmDZCc+IKtY1nrT2DGXTXlQ1OI+nFypaeda1+4yocl1T0dhyrOH9Ry7MgbZW+1DFusYbihcUWFG4rw/zJDyevyFF5v8eDoRI1+4zwof9M664iryN1Y+L7ys+VUeKh+9XqrhPo7UW/z0s8zeIF4GE7ha9POVlDWkteKHYjFjnc8W2Ijo2Gq8+F4FeIyCRrtdmXOMVAREQgQEgEFceY/NFWCl5u/CewFttmmmmyUQr8hVheTnj+AxPIzZg/COXna9CZsPJS3Ts8yhx7J133plVVY3D1MhrRXVMbz5kMO/tcFwBD8HFPEwIlfFVaxHwEFYG2vzmOb424cNUcSN3VBlvMLwk+QIfV4hrFOLSbh8Ig7TiIo3ytuXx9d4hbETYTKTMb7hSoUt+zqsIBaVAAyG2WCNPOkRD2wgXhcZ64SYOJ2cTaaJDKreYMUHAM49JQhFTxSaqWMv+Os2IOwitJialclY26lsVLDvhGVHFuvYFMMoWAYj5enG7jDdRfH67z4gq17VPlTBYokOrfahiXfNCylJQFBUR8C/BCI+16tl59573pMvL99novm3m83afEbzAsNQPpKHACzRlPkUC95L3Dk4dT6SBVR+nABMvGZoxihj5arplRDprH09w0lwQbs73oZRXPC+L+I4Ue1jn9bHVZ3gzY9axItBLBCTS9dJsa6wiIAIiMEAEfOgUX/IQWOJ8cXSFL7zkFsOKxALfbYQv3mbjcUPIoyXQ55iUtw/HE65iycq5HknA+VJpxQ7yvHB8Tj2SKOOxF1tRTi1CQwkhMSMcq5k8L1VNF0UBvKjGZoPNFRumRpuJuA/eAyD+DGHIh8z5z9vtg+Xto81GedvyuPkQ0FVXXbUWbhQf70U6Qpyt+Ikd158iXaOxsbHaeOONa11+4oknkhspv3nm//H4MvP5piiSYXkbYw4+fxShUlbRuKp1ae34XGZlKiPaeX5jXCYfVtzvKlh2wjOiinWNVxPexBgh7xQtaNb8fFx99dVZWH0z1u4zosp17cP3BqtaZat9qGJdUzDE8qvmFY6JixfwjPFVvlNz758pRekRmlk3Rce2+4yIc8rGBZW49ssvv5zdM2aE2CJyFZn3wG3FU7OVnHR5/eHvGaLdFVdcUSvCw7HMvy/ElHd+nP6Bl6neO7qquVQ7ItBLBCTS9dJsa6wiIAIiMEAEfAhMURhaUd4rBLS77rorqxaXqq7JUOIKdKmQWY6LQ1bwBLPKanyOWJgq1uDDjVLhsIbTfyH1ydbJjTbffPPVqOf1jwPwEMQLb80112yrCEFqiknejrcNRsjvmWeemczjhwckXgAIialNhvfOoi0EFcJO6btZ3hjb7YMXdLkWIdWpcBzGwCaJAiFx6K6vlpgX5vn2229nXoXmXXDuuef2Saj/+uuv1/FpV3z1RRqKvDUY94svvpjlYzRLFbaIN89xkn/WqOUMKvLc8+GH/elN5AsfNPJffWEAAA0/SURBVOPF5YVIqioj8qSMvFJsHNmw40VrVgXLTnhGVLGuvcdxI2/OvD8jPpdjmeT5cTvtPiOqXNe+ancrodRV/KlttQ9VrOu4anEq92X8TOZFilWpzhu/95ZMPbuq4ObbaPcZEXN47LHHwrTTTlvXTf99hw/KeAPj+UvoKUaaDRPIy46f0FVfSbeRJx1/F/kehLe8z7Hnr8cLTf7u28vLomeqP4/q5hSawHgpSwoQX6Cr7Jh0nAiIwP8nIJFOq0EEREAERKBSArEw1ehtuQ+RYrNpb6Q32WSTWn433vD6qox0mC+dhJqxGbQvhwhGqYIHVONEnDJvOj/gvGptHOMTmVM99sgjj0yywhvJPPriL+j+TT5vpRG64oTriJGEFGF5BSramaS4Uh+hvXGRDsJn8BSkQibGpt1vAhjX4YcfXusGYiIbDXLjMC5CNm0eEMl8ZV5+324f4jxwzAVzEpv39IsTmftwOM7zQh8FDOg3YpQPp06JdIT8Empkx+FNhaDVqjXjmce1ERGtom5KPCaEiRBms9iryXvaFImChGER8oT1p1Dhc4lxrbL5Br1ARhg5m1DC6L3hzco9yFyxgSRpvRUzqIJlJzwjqljXXnApynVYtMbxUrZwQCpX4qnbjLX7jKhyXft0CKwbhPhmcnQ1M+68Y1vtQxXr+rXXXqvzhEyJrqSqwIPVDDG8UfEjv0ZSRXmq4ObbaPcZERef4u+Lz3/rKxLbdcsU0OD+MO/mvHy3RSzilCJ5BYSsDYpUkDcWy0stwnc1XmCalQ1Z997ErXrhVj3vak8Eup2ARLpun0H1XwREQAQ6jIDfcCMAkJC86K0qoaeElGBeCPNeGbTDRnS66aYLiICIWniG8cbWrChvDsf4cEmPrCgh/oUXXhjwZsB80YkYuRcUEQ4R/sx8uAy/4ws+GxU87PCc4y20r7gWhyZWMb18ocf7yrzDENXo5/TTTx/wuqJiHV4sPnTYV7GLRQDetpP3yHLYPf/884EQUROtyBnH5mXEiBG17rfbBxrylQT5mTAh1gk5Dp955pkspNdEJT6Pw6/i8GO8PvCoI2SUdZqylEjHceS0M0GTTTxJ06m6Sl/ggXch/6WPrFszOHC9iRMn1n731ltv1W2OLrnkktpn3Dvw9ptf7zHEgeSPgj/iCpUdEVttLlIVh+PCH3leGH5jV7T+212jeC+OGTOm1kyZTS4HP/LII3XhWIyV0NnFF1884O3IBhuh0TxDWJeILV4kb5dlJzwjqljXvMDwYd2NPHNSc+7zmLXiednuM6LKde0rxTJWql9uscUWgRcyhPdxnyEKcm/mhfi3e1+004d21zV99wKXPU95WYZYeeONN9YV3okr4OLpxfMD8Yi/2TzHEMd95WqeWfPOO2/2e/7x4oiXdrPOOmu76Grnt/uMQPDkhRQpPMwQLPn7jScgfzdji/+GI0bytwImGGN94IEHas8lcn2yrqaYYoosLQj/5e+SVRAnYoDvEfwXS7HkJRH8jCV/h/g7b3+juR/5W2ZmAhzec7wUIZ2Bn5uyxWPiaIhWBMfKJlsNicAQIiCRbghNpoYiAiIgAp1AgPxWCBMYYgG53IoMMcNELe/Vk8p9hhiSKhrBRolKfHEYir8u3nRsQs3ji8+KvOj43At7RVU3fSW8OKcWGxQ2eKnkzCkuVtii6rn0Ff+sbUQLEzD89fjCz9txjE3KMsssUxPwEIL4gs8mwJvPQ8jvU6JOq32w6zz99NN9Qk/zOLHJwDMn9n7xif5T57IG/VzliXR4ZJXxFML7EBHXLPY+KTPPhHESemTGWkawNJGwqI2UN0Qs6uSFDvv5Sol9Zfpe9hjvtccaw5OzjOdSnMes6HqEl7Hhjp8L7bDslGdEu+v6nXfeqUsrUMYrKmbt1/Zuu+1Wq0Jcdg1wXDvPiCrXNc89QsKLKovT3yoKx+TxaacP7T4j6BM8EXoa/e3i7whFkXyRAV8tuJn5L/JYb6Ydf2y7z4j4b1uqH+TUtbQPXuCKUw+UHYP/LsRzC6/1Zs3nlPPfs6ydvO9TzCdRDd6TPu/a/iUFx7Sb+qHZMep4ERiqBCTSDdWZ1bhEQAREYJAImDcDX/QQnIYPH17YEzYihOwRqsamiCqqGN5FfGG3sL68RnhrzVviMht6nweG9vJy0dm1fNXNojAOn3Q9lWScN+AIlgg7eUbBALwDfcW2qqcwzq+Taj8OI8W7hZyAFi6IBwV9TZnfCOSFzLXSB38t5gyWKXHRjiOvGV50rMHYEE3JAYQYEBuhPqxFNnWIRFhR3iS8BWkrJRxzLpsgRBxf4deLUWXnN+Wd8Omnn2bXJpQ1ZfBnvadyC7KBJ6m/MUT8TFX2nTBhQlhqqaWy5tmsWyL5sv1u5ji8DtnomjUS0O04NsF43uGtkmfMA6J/nqjaDstOeUZUsa59hca8giRFc+rvbTwarSpmM+uAY1t9RlS9rhEueRb4nJvxWPozDJxrtdOHdta1jZOwV0Rs77XuGfACintrjjnmqENDCD8vxfKejXlrIvbIa3btpI6v4hmRErnsWohoVK7fYIMNapf3nqg+pUfZ8fiXgrEne9k2KKxl+Uv5ngVb7q0i47oUDZl77rkbXgbvdV9MqKhiesPGdIAIiEAdAYl0WhAiIAIiIAKVE0BgY9Pv36wXXQQhiPA0vuj6UDS+XCOAERJKWCrhmLylplADFecQ6MqGxsQebYQu+TDTvP4R1skXbkIZ8yqh0n9CYMjPRi6wlEcfOc8QbHjTTE44zplzzjmzsSAq8WU6VQG36slBVCBMC+8AxENCXvmHOMgX7pEjR/a5JH1GDNp6663rEu+n+gYr3sLjScccpayVPvh2WCuIunAkkTdhPmwSCUFiQ2RhQkXs8BRiXSHucjwFBYw/ohUbHNYWol2cQ9C3y1pHyEOchid94TxCmOhLLBTSd9YBggLXo23+6/9/sskmq/2OuSF8k9/FxsaL8SNcWq41wscQUcnDFucd9OdzP7H5Y+3hKZlnHENoFhVl88TZqtZo7PEC+2233baP12bqeoTZ471DGCJzMssss2Th1txXrOsiL1vaa4dlJz0j2lnXrCPLIWpVt5uZW57Xp59+eibM8HxFKG7VWn1G9Me6Zm1R/ZIXRghfw4YNy7yMEDXHjRvX6hCbOq/VPrSzrq2DhGnyrIUtYdE803jO8LwlTDPv+UgFUp539MH+EV7Js4//Yvb//EzBIp8ioSlAJQ5u9xnB3zb+7uDBTIg+eVdZ5zzrGR8vFXkGxUWJ+FuPaMkYPQd+tt95LqQ2YH15rjzT+H6ROt+3Yzx5McTfjthIFUIfmUuEV+5RvoNwPb7jxLlkU1jpA1VuSQXiU2QgZPoXUiWmRIeIgAjkEJBIp6UhAiIgAiLQEwR8Em4G3MiLriegaJAi0EEETNxBFPSWClPtoG6rKyIgAiKQEcA7meiBoVrdlAJTFC7y4hzjbqWas5aMCIhAPgGJdFodIiACIiACQ54AHh54PFh4Hx5hhMjJREAEOotASqhba621WsrJ1FkjU29EQAREoLsJ4Km74oor1g2CohM+7LW7R6jei0BnEJBI1xnzoF6IgAiIgAj0I4Hzzjsvq2ZqhqdO2TDZfuyWmhYBEUgQIJyKzSDhU+Q9IuSV0DqZCIiACIjA4BI45ZRTsqIi5CMkV2/ZtCaD22tdXQS6i4BEuu6aL/VWBERABESgSQLkxSEZsiWw7u9E3012T4eLgAiIgAiIgAiIgAiIgAiIQEZAIp0WggiIgAiIwJAmcM4554TDDjusNkZ50Q3p6dbgREAEREAEREAEREAERKBrCUik69qpU8dFQAREQAQaEaCq2qKLLlrzottmm23CgQce2Og0fS4CIiACIiACIiACIiACIiACA05AIt2AI9cFRUAEREAEBorAyy+/nOVMMXvooYfCzDPPPFCX13VEQAREQAREQAREQAREQAREoDQBiXSlUelAERABERCBbiRw1FFHhauuuirsu+++Yb311uvGIajPIiACIiACIiACIiACIiACPUBAIl0PTLKGKAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIi0NkEJNJ19vyodyIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAj1AQCJdD0yyhigCIiACIiACIiACIiACIiACIiACIiACItDZBCTSdfb8qHciIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAI9QEAiXQ9MsoYoAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiLQ2QQk0nX2/Kh3IiACIiACIiACIiACIiACIiACIiACIiACPUBAIl0PTLKGKAIiIAIiIAIiIAIiIAIiIAIiIAIiIAIi0NkEJNJ19vyodyIgAiIgAiIgAiIgAiIgAiIgAiIgAiIgAj1AQCJdD0yyhigCIiACIiACIiACIiACIiACIiACIiACItDZBCTSdfb8qHciIAIiIAIiIAIiIAIiIAIiIAIiIAIiIAI9QEAiXQ9MsoYoAiIgAiIgAiIgAiIgAiIgAiIgAiIgAiLQ2QT+H5oMd4QfqfUlAAAAAElFTkSuQmCC"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Research Agent with MCP\n",
    "\n",
    "*The goal of research is to gather the context requested by the research brief.*\n",
    "\n",
    "Here is our overall research flow:\n",
    "\n",
    "![Screenshot 2025-07-16 at 1.49.32 PM.png](attachment:d63282d4-d236-4425-9d5f-7885573f2989.png)\n",
    "\n",
    "We built an [agent](https://langchain-ai.github.io/langgraph/tutorials/workflows/#agent) that will a custom search tool. But, we can also use the [Model Context Protocol (MCP)](https://modelcontextprotocol.io/specification/2025-06-18/architecture) as another way to access tools! MCP servers provide a standard protocol for accessing tools. [LangChain MCP Adapters](https://github.com/langchain-ai/langchain-mcp-adapters) provide a seamless bridge between the Model Context Protocol (MCP) and LangChain/LangGraph ecosystems. This library enables compatibility between MCP servers and our LangGraph agent. \n",
    "\n",
    "Let's pick one example MCP server and see how it works! The [Filesystem MCP Server](https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem) provides secure, controlled access to local file systems with granular permission management.\n",
    "\n",
    "**What It Provides:**\n",
    "- **File operations** with strict access control\n",
    "- **Directory management** with dynamic permissions\n",
    "- **Search capabilities** across allowed directories\n",
    "- **Metadata access** for files and directories\n",
    "\n",
    "**Available Tools:**\n",
    "- **File Operations**: `read_file`, `write_file`, `edit_file`, `read_multiple_files`\n",
    "- **Directory Management**: `create_directory`, `list_directory`, `move_file`\n",
    "- **Search & Discovery**: `search_files`, `get_file_info`, `list_allowed_directories`\n",
    "\n",
    "![mcp.png](attachment:dee39e66-0306-441a-9267-12cd91e7f95e.png)\n",
    "\n",
    "### Prompt\n",
    "\n",
    "First, we'll define a prompt that instructs our agent to use available search tools. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #000080; text-decoration-color: #000080\">╭──────────────────────────────────────── </span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Research Agent Instructions MCP</span><span style=\"color: #000080; text-decoration-color: #000080\"> ────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  You are a research assistant conducting research on the user's input topic using local files. For context,     <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  today's date is {date}.                                                                                        <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;Task&gt;</span>                                                                                                         <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  Your job is to use file system tools to gather information from local research files.                          <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  You can use any of the tools provided to you to find and read files that help answer the research question.    <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  You can call these tools in series or in parallel, your research is conducted in a tool-calling loop.          <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;/Task&gt;</span>                                                                                                        <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;Available Tools&gt;</span>                                                                                              <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  You have access to file system tools and thinking tools:                                                       <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - **list_allowed_directories**: See what directories you can access                                            <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - **list_directory**: List files in directories                                                                <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - **read_file**: Read individual files                                                                         <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - **read_multiple_files**: Read multiple files at once                                                         <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - **search_files**: Find files containing specific content                                                     <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - **think_tool**: For reflection and strategic planning during research                                        <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  **CRITICAL: Use think_tool after reading files to reflect on findings and plan next steps**                    <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;/Available Tools&gt;</span>                                                                                             <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;Instructions&gt;</span>                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  Think like a human researcher with access to a document library. Follow these steps:                           <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  1. **Read the question carefully** - What specific information does the user need?                             <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  2. **Explore available files** - Use list_allowed_directories and list_directory to understand what's          <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  available                                                                                                      <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  3. **Identify relevant files** - Use search_files if needed to find documents matching the topic               <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  4. **Read strategically** - Start with most relevant files, use read_multiple_files for efficiency             <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  5. **After reading, pause and assess** - Do I have enough to answer? What's still missing?                     <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  6. **Stop when you can answer confidently** - Don't keep reading for perfection                                <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;/Instructions&gt;</span>                                                                                                <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;Hard Limits&gt;</span>                                                                                                  <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  **File Operation Budgets** (Prevent excessive file reading):                                                   <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - **Simple queries**: Use 3-4 file operations maximum                                                          <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - **Complex queries**: Use up to 6 file operations maximum                                                     <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - **Always stop**: After 6 file operations if you cannot find the right information                            <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  **Stop Immediately When**:                                                                                     <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - You can answer the user's question comprehensively from the files                                            <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - You have comprehensive information from 3+ relevant files                                                    <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - Your last 2 file reads contained similar information                                                         <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;/Hard Limits&gt;</span>                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;Show Your Thinking&gt;</span>                                                                                           <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  After reading files, use think_tool to analyze what you found:                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - What key information did I find?                                                                             <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - What's missing?                                                                                              <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - Do I have enough to answer the question comprehensively?                                                     <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - Should I read more files or provide my answer?                                                               <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  - Always cite which files you used for your information                                                        <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>  <span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">&lt;/Show Your Thinking&gt;</span>                                                                                          <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span>                                                                                                                 <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[34m╭─\u001b[0m\u001b[34m───────────────────────────────────────\u001b[0m\u001b[34m \u001b[0m\u001b[1;32mResearch Agent Instructions MCP\u001b[0m\u001b[34m \u001b[0m\u001b[34m───────────────────────────────────────\u001b[0m\u001b[34m─╮\u001b[0m\n",
       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  You are a research assistant conducting research on the user's input topic using local files. For context,     \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  today's date is {date}.                                                                                        \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  \u001b[1;34m<Task>\u001b[0m                                                                                                         \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  Your job is to use file system tools to gather information from local research files.                          \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  You can use any of the tools provided to you to find and read files that help answer the research question.    \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  You can call these tools in series or in parallel, your research is conducted in a tool-calling loop.          \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  \u001b[1;34m</Task>\u001b[0m                                                                                                        \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  \u001b[1;34m<Available Tools>\u001b[0m                                                                                              \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  You have access to file system tools and thinking tools:                                                       \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - **list_allowed_directories**: See what directories you can access                                            \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - **list_directory**: List files in directories                                                                \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - **read_file**: Read individual files                                                                         \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - **read_multiple_files**: Read multiple files at once                                                         \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - **search_files**: Find files containing specific content                                                     \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - **think_tool**: For reflection and strategic planning during research                                        \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  **CRITICAL: Use think_tool after reading files to reflect on findings and plan next steps**                    \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  \u001b[1;34m</Available Tools>\u001b[0m                                                                                             \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  \u001b[1;34m<Instructions>\u001b[0m                                                                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  Think like a human researcher with access to a document library. Follow these steps:                           \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  1. **Read the question carefully** - What specific information does the user need?                             \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  2. **Explore available files** - Use list_allowed_directories and list_directory to understand what's          \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  available                                                                                                      \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  3. **Identify relevant files** - Use search_files if needed to find documents matching the topic               \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  4. **Read strategically** - Start with most relevant files, use read_multiple_files for efficiency             \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  5. **After reading, pause and assess** - Do I have enough to answer? What's still missing?                     \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  6. **Stop when you can answer confidently** - Don't keep reading for perfection                                \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  \u001b[1;34m</Instructions>\u001b[0m                                                                                                \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  \u001b[1;34m<Hard Limits>\u001b[0m                                                                                                  \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  **File Operation Budgets** (Prevent excessive file reading):                                                   \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - **Simple queries**: Use 3-4 file operations maximum                                                          \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - **Complex queries**: Use up to 6 file operations maximum                                                     \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - **Always stop**: After 6 file operations if you cannot find the right information                            \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  **Stop Immediately When**:                                                                                     \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - You can answer the user's question comprehensively from the files                                            \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - You have comprehensive information from 3+ relevant files                                                    \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - Your last 2 file reads contained similar information                                                         \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  \u001b[1;34m</Hard Limits>\u001b[0m                                                                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  \u001b[1;34m<Show Your Thinking>\u001b[0m                                                                                           \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  After reading files, use think_tool to analyze what you found:                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - What key information did I find?                                                                             \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - What's missing?                                                                                              \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - Do I have enough to answer the question comprehensively?                                                     \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - Should I read more files or provide my answer?                                                               \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  - Always cite which files you used for your information                                                        \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m  \u001b[1;34m</Show Your Thinking>\u001b[0m                                                                                          \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m                                                                                                                 \u001b[34m│\u001b[0m\n",
       "\u001b[34m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from utils import show_prompt\n",
    "from deep_research_from_scratch.prompts import research_agent_prompt_with_mcp\n",
    "show_prompt(research_agent_prompt_with_mcp, \"Research Agent Instructions MCP\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Research Tool\n",
    "\n",
    "Now, we'll use the `Filesystem MCP Server` to access research tools.\n",
    "\n",
    "When using MCP tools with LangChain, you must use async methods because the MCP protocol is inherently asynchronous:\n",
    "- Server communication uses async JSON-RPC over stdio/http\n",
    "- Tool invocations involve network/IPC calls that can be slow\n",
    "- Async enables non-blocking, concurrent operations\n",
    "\n",
    "With this in mind, LangChain MCP Adapters are designed for async-only operation:\n",
    "- Tools are wrapped as async StructuredTools\n",
    "- Sync invocation is intentionally not implemented\n",
    "- This ensures consistent async behavior across all MCP tools\n",
    "\n",
    "Async enables:\n",
    "- Concurrent tool execution\n",
    "- Non-blocking server communication\n",
    "- Better resource utilization\n",
    "- Responsive applications\n",
    "\n",
    "MCP servers run as subprocesses:\n",
    "- Communication happens over pipes (stdin/stdout)\n",
    "- These I/O operations are naturally async\n",
    "- Blocking sync calls would freeze the entire process\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       "│ <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">Creating MCP client...</span> │\n",
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       "╭────────────────────────╮\n",
       "│ \u001b[1;33mCreating MCP client...\u001b[0m │\n",
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       "\u001b[32m✓ MCP client created successfully!\u001b[0m\n"
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       "│ <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">Getting tools...</span> │\n",
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       "╭──────────────────╮\n",
       "│ \u001b[1;33mGetting tools...\u001b[0m │\n",
       "╰──────────────────╯\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-style: italic\">                                              Available MCP Tools                                               </span>\n",
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> Tool Name                 </span>┃<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\"> Description                                                                      </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> read_file                 </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Read the complete contents of a file as text. DEPRECATED: Use read_text_file ... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> read_text_file            </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Read the complete contents of a file from the file system as text. Handles va... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> read_media_file           </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Read an image or audio file. Returns the base64 encoded data and MIME type. O... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> read_multiple_files       </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Read the contents of multiple files simultaneously. This is more efficient th... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> write_file                </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Create a new file or completely overwrite an existing file with new content. ... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> edit_file                 </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Make line-based edits to a text file. Each edit replaces exact line sequences... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> create_directory          </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Create a new directory or ensure a directory exists. Can create multiple nest... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> list_directory            </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Get a detailed listing of all files and directories in a specified path. Resu... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> list_directory_with_sizes </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Get a detailed listing of all files and directories in a specified path, incl... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> directory_tree            </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Get a recursive tree view of files and directories as a JSON structure. Each ... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> move_file                 </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Move or rename files and directories. Can move files between directories and ... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> search_files              </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Recursively search for files and directories matching a pattern. Searches thr... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> get_file_info             </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Retrieve detailed metadata about a file or directory. Returns comprehensive i... </span>│\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\"> list_allowed_directories  </span>│<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\"> Returns the list of root directories that this server is allowed to access. U... </span>│\n",
       "└───────────────────────────┴──────────────────────────────────────────────────────────────────────────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[3m                                              Available MCP Tools                                               \u001b[0m\n",
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1;35m \u001b[0m\u001b[1;35mTool Name                \u001b[0m\u001b[1;35m \u001b[0m┃\u001b[1;35m \u001b[0m\u001b[1;35mDescription                                                                     \u001b[0m\u001b[1;35m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│\u001b[36m \u001b[0m\u001b[36mread_file                \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mRead the complete contents of a file as text. DEPRECATED: Use read_text_file ...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36mread_text_file           \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mRead the complete contents of a file from the file system as text. Handles va...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36mread_media_file          \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mRead an image or audio file. Returns the base64 encoded data and MIME type. O...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36mread_multiple_files      \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mRead the contents of multiple files simultaneously. This is more efficient th...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36mwrite_file               \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mCreate a new file or completely overwrite an existing file with new content. ...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36medit_file                \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mMake line-based edits to a text file. Each edit replaces exact line sequences...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36mcreate_directory         \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mCreate a new directory or ensure a directory exists. Can create multiple nest...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36mlist_directory           \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mGet a detailed listing of all files and directories in a specified path. Resu...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36mlist_directory_with_sizes\u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mGet a detailed listing of all files and directories in a specified path, incl...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36mdirectory_tree           \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mGet a recursive tree view of files and directories as a JSON structure. Each ...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36mmove_file                \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mMove or rename files and directories. Can move files between directories and ...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36msearch_files             \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mRecursively search for files and directories matching a pattern. Searches thr...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36mget_file_info            \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mRetrieve detailed metadata about a file or directory. Returns comprehensive i...\u001b[0m\u001b[37m \u001b[0m│\n",
       "│\u001b[36m \u001b[0m\u001b[36mlist_allowed_directories \u001b[0m\u001b[36m \u001b[0m│\u001b[37m \u001b[0m\u001b[37mReturns the list of root directories that this server is allowed to access. U...\u001b[0m\u001b[37m \u001b[0m│\n",
       "└───────────────────────────┴──────────────────────────────────────────────────────────────────────────────────┘\n"
      ]
     },
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    },
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     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">✓ Successfully retrieved </span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">14</span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\"> tools from MCP server</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;32m✓ Successfully retrieved \u001b[0m\u001b[1;32m14\u001b[0m\u001b[1;32m tools from MCP server\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Simple MCP Example\n",
    "import os\n",
    "from langchain_mcp_adapters.client import MultiServerMCPClient\n",
    "from rich.console import Console\n",
    "from rich.panel import Panel\n",
    "from rich.table import Table\n",
    "\n",
    "console = Console()\n",
    "\n",
    "# Get the absolute path to our sample research docs\n",
    "sample_docs_path = os.path.abspath(\"./files/\")\n",
    "console.print(f\"[bold blue]Sample docs path:[/bold blue] {sample_docs_path}\")\n",
    "\n",
    "# Check if the directory exists\n",
    "if os.path.exists(sample_docs_path):\n",
    "    console.print(f\"[green]✓ Directory exists with files:[/green] {os.listdir(sample_docs_path)}\")\n",
    "else:\n",
    "    console.print(\"[red]✗ Directory does not exist![/red]\")\n",
    "\n",
    "# MCP Client configuration - filesystem server for local document access\n",
    "mcp_config = {\n",
    "    \"filesystem\": {\n",
    "        \"command\": \"npx\",\n",
    "        \"args\": [\n",
    "            \"-y\",  # Auto-install if needed\n",
    "            \"@modelcontextprotocol/server-filesystem\",\n",
    "            sample_docs_path\n",
    "        ],\n",
    "        \"transport\": \"stdio\"\n",
    "    }\n",
    "}\n",
    "\n",
    "console.print(Panel(\"[bold yellow]Creating MCP client...[/bold yellow]\", expand=False))\n",
    "client = MultiServerMCPClient(mcp_config)\n",
    "console.print(\"[green]✓ MCP client created successfully![/green]\")\n",
    "\n",
    "# Test getting tools\n",
    "console.print(Panel(\"[bold yellow]Getting tools...[/bold yellow]\", expand=False))\n",
    "tools = await client.get_tools()\n",
    "\n",
    "# Create a rich table for tool display\n",
    "table = Table(title=\"Available MCP Tools\", show_header=True, header_style=\"bold magenta\")\n",
    "table.add_column(\"Tool Name\", style=\"cyan\", width=25)\n",
    "table.add_column(\"Description\", style=\"white\", width=80)\n",
    "\n",
    "for tool in tools:\n",
    "    # Truncate long descriptions for better display\n",
    "    description = tool.description[:77] + \"...\" if len(tool.description) > 80 else tool.description\n",
    "    table.add_row(tool.name, description)\n",
    "\n",
    "console.print(table)\n",
    "console.print(f\"[bold green]✓ Successfully retrieved {len(tools)} tools from MCP server[/bold green]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Agent\n",
    "\n",
    "Now, we'll define our agent again. But, we'll include the MCP server! \n",
    "\n",
    "The Model Context Protocol (MCP) is fundamentally designed around asynchronous operations, and this requirement is unavoidable due to several architectural factors:\n",
    "\n",
    "MCP servers run as separate subprocesses that communicate via:\n",
    "- **stdin/stdout pipes** (for local servers)\n",
    "- **HTTP/WebSocket connections** (for remote servers)\n",
    "\n",
    "Tool operations often involve:\n",
    "- File system operations (reading, writing, searching)\n",
    "- Network requests (for remote MCP servers)\n",
    "- Database queries (for data-backed servers)\n",
    "- External API calls\n",
    "\n",
    "These operations have variable latency and benefit from non-blocking async execution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting ../src/deep_research_from_scratch/research_agent_mcp.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile ../src/deep_research_from_scratch/research_agent_mcp.py\n",
    "\n",
    "\"\"\"Research Agent with MCP Integration.\n",
    "\n",
    "This module implements a research agent that integrates with Model Context Protocol (MCP)\n",
    "servers to access tools and resources. The agent demonstrates how to use MCP filesystem\n",
    "server for local document research and analysis.\n",
    "\n",
    "Key features:\n",
    "- MCP server integration for tool access\n",
    "- Async operations for concurrent tool execution (required by MCP protocol)\n",
    "- Filesystem operations for local document research\n",
    "- Secure directory access with permission checking\n",
    "- Research compression for efficient processing\n",
    "- Lazy MCP client initialization for LangGraph Platform compatibility\n",
    "\"\"\"\n",
    "\n",
    "import os\n",
    "\n",
    "from typing_extensions import Literal\n",
    "\n",
    "from langchain.chat_models import init_chat_model\n",
    "from langchain_core.messages import SystemMessage, HumanMessage, ToolMessage, filter_messages\n",
    "from langchain_mcp_adapters.client import MultiServerMCPClient\n",
    "from langgraph.graph import StateGraph, START, END\n",
    "\n",
    "from deep_research_from_scratch.prompts import research_agent_prompt_with_mcp, compress_research_system_prompt, compress_research_human_message\n",
    "from deep_research_from_scratch.state_research import ResearcherState, ResearcherOutputState\n",
    "from deep_research_from_scratch.utils import get_today_str, think_tool, get_current_dir\n",
    "\n",
    "# ===== CONFIGURATION =====\n",
    "\n",
    "# MCP server configuration for filesystem access\n",
    "mcp_config = {\n",
    "    \"filesystem\": {\n",
    "        \"command\": \"npx\",\n",
    "        \"args\": [\n",
    "            \"-y\",  # Auto-install if needed\n",
    "            \"@modelcontextprotocol/server-filesystem\",\n",
    "            str(get_current_dir() / \"files\")  # Path to research documents\n",
    "        ],\n",
    "        \"transport\": \"stdio\"  # Communication via stdin/stdout\n",
    "    }\n",
    "}\n",
    "\n",
    "# Global client variable - will be initialized lazily\n",
    "_client = None\n",
    "\n",
    "def get_mcp_client():\n",
    "    \"\"\"Get or initialize MCP client lazily to avoid issues with LangGraph Platform.\"\"\"\n",
    "    global _client\n",
    "    if _client is None:\n",
    "        _client = MultiServerMCPClient(mcp_config)\n",
    "    return _client\n",
    "\n",
    "# Initialize models\n",
    "compress_model = init_chat_model(model=\"openai:gpt-4.1\", max_tokens=32000)\n",
    "model = init_chat_model(model=\"anthropic:claude-sonnet-4-20250514\")\n",
    "\n",
    "# ===== AGENT NODES =====\n",
    "\n",
    "async def llm_call(state: ResearcherState):\n",
    "    \"\"\"Analyze current state and decide on tool usage with MCP integration.\n",
    "\n",
    "    This node:\n",
    "    1. Retrieves available tools from MCP server\n",
    "    2. Binds tools to the language model\n",
    "    3. Processes user input and decides on tool usage\n",
    "\n",
    "    Returns updated state with model response.\n",
    "    \"\"\"\n",
    "    # Get available tools from MCP server\n",
    "    client = get_mcp_client()\n",
    "    mcp_tools = await client.get_tools()\n",
    "\n",
    "    # Use MCP tools for local document access\n",
    "    tools = mcp_tools + [think_tool]\n",
    "\n",
    "    # Initialize model with tool binding\n",
    "    model_with_tools = model.bind_tools(tools)\n",
    "\n",
    "    # Process user input with system prompt\n",
    "    return {\n",
    "        \"researcher_messages\": [\n",
    "            model_with_tools.invoke(\n",
    "                [SystemMessage(content=research_agent_prompt_with_mcp.format(date=get_today_str()))] + state[\"researcher_messages\"]\n",
    "            )\n",
    "        ]\n",
    "    }\n",
    "\n",
    "async def tool_node(state: ResearcherState):\n",
    "    \"\"\"Execute tool calls using MCP tools.\n",
    "\n",
    "    This node:\n",
    "    1. Retrieves current tool calls from the last message\n",
    "    2. Executes all tool calls using async operations (required for MCP)\n",
    "    3. Returns formatted tool results\n",
    "\n",
    "    Note: MCP requires async operations due to inter-process communication\n",
    "    with the MCP server subprocess. This is unavoidable.\n",
    "    \"\"\"\n",
    "    tool_calls = state[\"researcher_messages\"][-1].tool_calls\n",
    "\n",
    "    async def execute_tools():\n",
    "        \"\"\"Execute all tool calls. MCP tools require async execution.\"\"\"\n",
    "        # Get fresh tool references from MCP server\n",
    "        client = get_mcp_client()\n",
    "        mcp_tools = await client.get_tools()\n",
    "        tools = mcp_tools + [think_tool]\n",
    "        tools_by_name = {tool.name: tool for tool in tools}\n",
    "\n",
    "        # Execute tool calls (sequentially for reliability)\n",
    "        observations = []\n",
    "        for tool_call in tool_calls:\n",
    "            tool = tools_by_name[tool_call[\"name\"]]\n",
    "            if tool_call[\"name\"] == \"think_tool\":\n",
    "                # think_tool is sync, use regular invoke\n",
    "                observation = tool.invoke(tool_call[\"args\"])\n",
    "            else:\n",
    "                # MCP tools are async, use ainvoke\n",
    "                observation = await tool.ainvoke(tool_call[\"args\"])\n",
    "            observations.append(observation)\n",
    "\n",
    "        # Format results as tool messages\n",
    "        tool_outputs = [\n",
    "            ToolMessage(\n",
    "                content=observation,\n",
    "                name=tool_call[\"name\"],\n",
    "                tool_call_id=tool_call[\"id\"],\n",
    "            )\n",
    "            for observation, tool_call in zip(observations, tool_calls)\n",
    "        ]\n",
    "\n",
    "        return tool_outputs\n",
    "\n",
    "    messages = await execute_tools()\n",
    "\n",
    "    return {\"researcher_messages\": messages}\n",
    "\n",
    "def compress_research(state: ResearcherState) -> dict:\n",
    "    \"\"\"Compress research findings into a concise summary.\n",
    "\n",
    "    Takes all the research messages and tool outputs and creates\n",
    "    a compressed summary suitable for further processing or reporting.\n",
    "\n",
    "    This function filters out think_tool calls and focuses on substantive\n",
    "    file-based research content from MCP tools.\n",
    "    \"\"\"\n",
    "    \n",
    "    system_message = compress_research_system_prompt.format(date=get_today_str())\n",
    "    messages = [SystemMessage(content=system_message)] + state.get(\"researcher_messages\", []) + [HumanMessage(content=compress_research_human_message)]\n",
    "\n",
    "    response = compress_model.invoke(messages)\n",
    "\n",
    "    # Extract raw notes from tool and AI messages\n",
    "    raw_notes = [\n",
    "        str(m.content) for m in filter_messages(\n",
    "            state[\"researcher_messages\"], \n",
    "            include_types=[\"tool\", \"ai\"]\n",
    "        )\n",
    "    ]\n",
    "\n",
    "    return {\n",
    "        \"compressed_research\": str(response.content),\n",
    "        \"raw_notes\": [\"\\n\".join(raw_notes)]\n",
    "    }\n",
    "\n",
    "# ===== ROUTING LOGIC =====\n",
    "\n",
    "def should_continue(state: ResearcherState) -> Literal[\"tool_node\", \"compress_research\"]:\n",
    "    \"\"\"Determine whether to continue with tool execution or compress research.\n",
    "\n",
    "    Determines whether to continue with tool execution or compress research\n",
    "    based on whether the LLM made tool calls.\n",
    "    \"\"\"\n",
    "    messages = state[\"researcher_messages\"]\n",
    "    last_message = messages[-1]\n",
    "\n",
    "    # Continue to tool execution if tools were called\n",
    "    if last_message.tool_calls:\n",
    "        return \"tool_node\"\n",
    "    # Otherwise, compress research findings\n",
    "    return \"compress_research\"\n",
    "\n",
    "# ===== GRAPH CONSTRUCTION =====\n",
    "\n",
    "# Build the agent workflow\n",
    "agent_builder_mcp = StateGraph(ResearcherState, output_schema=ResearcherOutputState)\n",
    "\n",
    "# Add nodes to the graph\n",
    "agent_builder_mcp.add_node(\"llm_call\", llm_call)\n",
    "agent_builder_mcp.add_node(\"tool_node\", tool_node)\n",
    "agent_builder_mcp.add_node(\"compress_research\", compress_research)\n",
    "\n",
    "# Add edges to connect nodes\n",
    "agent_builder_mcp.add_edge(START, \"llm_call\")\n",
    "agent_builder_mcp.add_conditional_edges(\n",
    "    \"llm_call\",\n",
    "    should_continue,\n",
    "    {\n",
    "        \"tool_node\": \"tool_node\",        # Continue to tool execution\n",
    "        \"compress_research\": \"compress_research\",  # Compress research findings\n",
    "    },\n",
    ")\n",
    "agent_builder_mcp.add_edge(\"tool_node\", \"llm_call\")  # Loop back for more processing\n",
    "agent_builder_mcp.add_edge(\"compress_research\", END)\n",
    "\n",
    "# Compile the agent\n",
    "agent_mcp = agent_builder_mcp.compile()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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mI29/VqvP+CYWu3v3bmFhYd++fR89etSiRQvr1AY+HmT+befPnw8KCqJSqWQymcvlYl0OysrKio2NdXNz27p1K9a1GPfHH3+cO3dux44dTKaRm20AvIH9+f/YuHHjuXPnBAIBn8/HQ+ARQvv37y8qKsrKyrp8+TLWtRgXExOzePFiuVxeVVV18uRJrMsBdYDMI4TQs2fPEhMTEUIDBw5cuXJlzd3gMJeVlXX79m2EkFgs3r17N9bl1MrPz08gELDZ7JSUlHnz5mFdDjCF6JnX6XQlJSXz588PDg5GCLm7u2Nd0X8kJibm5+cbHmdnZ1+6dAnrikyhUCiLFi2aPn06QmjPnj379u3DuiJgBHEzr1Qqly9fLpfLORzO3r17fX19sa7obS9evLh7927NU5w39TX4fL6hx5Sfn4/b/REiI27m582b5+fnx+FwHBwcsK7FuMTExNzc3Den4L+pr8FkMmfOnPnpp58ihPr167dz506sKwL/INxx+7/++kskEk2ePBnrQuoWFRVVUPCfH7rr9frAwMCEhATsivoQer0+ISFh5MiReXl5QqGQw+FgXRGhESvzGRkZZ8+ejY2Nfd+7vmNrzpw5oaGh4eHhWBfysV69ejVs2LDFixeHhoZiXQtx2dJH/4Olp6cPGjQIIRQQEDB9+nTbCrw98fT0vHLlikAgQAglJSUVFxdjXRER2fmnv6SkBCF0/fr1NWvWIISo1vopGzChdevWCCEvL6+YmBiRSKTT2elvmPHKbjMvl8unTZt2584dhNCkSZMaN26MdUXgPzp06HDy5EkGgyGXy2fOnPnq1SusKyIKO8x8eXk5Qujp06cDBgyIjIzEuhxgCovF4nA4ERERu3btQgiVlZVhXZH9s7fMJyQkxMTEIISCgoK6du2KdTmgXrp37z5nzhyEUEpKyoQJEyorK7GuyJ7ZT+YzMzMRQs7OzkeOHMG6FvCB+vTpExMTk5OTgxC6d+8e1uXYJ3vIfH5+/meffWY46RgREYF1OeCjBAcHt23bFiF06tSpb7/9Futy7JBtH8e+dOlSt27dqqurz507x2KxsC4HmFNcXNyLFy8QQg8ePHj16lXv3r2xrshO2HA7Hxsba7jmrHnz5hB4u9S0aVOEULNmzW7evAm/3jUX22vnMzMzq6qqQkJCYmNj4QwcETCZzMWLF0skEoTQsmXLfH19o6OjsS7KhtlYO3/79u2VK1cavv4h8IRiGMJk6tSp+fn5r169UqkINwaxudhG5quqqjZt2mT48eauXbucnZ2xrghgw8HBYebMmR4eHnq9PiQk5NSpU1hXZHtsI/MjR4709/fH4ZgWABMkEonBYFy9elWr1SKEUlNTpVIi3nHkw+A68zt37jQMunD48OGwsDCsywH4QqPRDL+zZDAYERERT548wboi24DfzO/fv18sFsNFl6BOLVu2vHLliuHczZYtW0pLS7GuCNdwl/mUlJQZM2YYBleZOnUq1uUAm9GoUSOEkI+Pz5QpU7CuBdfwlXmFQnH69OmZM2caOmxYl4MLFy9efP78eWBgINaF2Ibw8HDDEMZHjx7VaKx00xHbQqxxcmxLcXHxkiVLmEzm/PnzHR0dsS7HxnTp0uXMmTNsNhvrQnAHX+28YX9MoVBgXQX2Nm3aFBMTM3z48NWrV0PgP0C/fv1giBSjcJf5Bw8epKenY10Fli5evBgWFsZgME6ePNmpUyesy7FVM2bMoNPpWFeBR7j7IpwwYQJh36qaznxSUpJhlHjwwY4ePdqnTx9o6t8F+/N48euvv/79999xcXHQtpsF7M/XBnd9e7FYvHbtWqyrsKoLFy6EhYWxWCzozJsR7M/XBo/tfI8ePQ4cOGAYEdm+FRUVLV26lMVizZ07FzrzwDrwmPm0tDQvLy+hUIh1IZb166+/njp1au7cudC2WwLsz9cGd317w/CV9h34ms78iRMnIPAWsnr1arje1ig8fgs+fPjwzp07Y8aMwboQ8ysqKlqyZAmbzYYj85YG+/O1wWPfvri4OCYm5uTJk1gXYmYbN248ffp0XFxcSEgI1rUA4sJj375hw4bLli2zpx9LJycnh4WFcTicEydOQOCtA35vXxs8tvP2pLCwcOnSpRwOZ86cOdCZtyY4P18bnO7wHDlyhEQi9evXD+tCPsrGjRvPnDkzd+5caNutD/bna4PHvj1CSCAQGEbIsVHJycndu3fncDjHjx+HwGMCfm9fG5x+EX766aeGIRBsTmFh4ZIlSxwcHA4fPszj8bAuh7jg/HxtcL0/HxUVJZVKRSJRcHDwb7/9hnU5dYuPjz979mxcXFzHjh2xroWghg4dSqPRyGTy48ePfX19aTQaiURycHDYvHkz1qXhBe6+Bbt27SqTyXQ6HUKITCYbBjnF/w9XkpOTly5dOnLkyOPHj2NdC6E9f/7c8LFBCGVlZRk+RbNmzcK6LhzBXea9vb0zMzMpFErNFKFQGBQUhGlRpkBnHlfatWuXmppKIpFqpvj4+AwePBjTovAFd8fw1q5d6+3t/eYUR0dH3GY+Pj5+/Pjxo0aNWrVqFQQeD0aMGPHm1Vl0On3YsGGYVoQ7uMu8i4vLtGnTDDcqQgjpdDrD3SzwxnBk3tHR8fjx47D3jh+hoaE+Pj41T729vW39jK/Z4a5vjxDq1q1bZmZmQkKCRqOhUCgdOnTAuqL/KCgoWLp0KXTmcWvEiBE5OTkikYjBYEAj/y7ctfMGkydPDg4O1uv1DRo0aN26Ndbl/Cs+Pn7ixInQmcez0NDQJk2aGO5u2LdvX6zLwZ16tfMatU5erbN8Mf+xbNG6mJgYR0fHBgLvqkrsfzidmpq6atWqQYMG/bXzEJlSjxfgjKRcTSKT6rGgPRjc/+tXueVDBo7CwyfHOvQ6PVdIq8+SdZyff3xb8uCquKJYxXbA4GOu1ekoZLz0RBRKJYPBMITG0ZkmKlUFBDt2jsT7HXLLC5V3zlVmP6z2aMoWlcD15HbLwYlWlC33CeS07c5382GZWNJU5m+frSgrVAeFOjk61ev7g1BkVZqC59IX9yWDv/ckU3Dafha/VJz7q6Tr4IY8ZzoFr0UCc9Hr9eLX6utHSzpFChsF1HpxUa2ZTzldISnXhES6WLJIm/fqufThlYoh072wLsSI0nzF2d2l/SZ512NZYFdO/fkqJMLJu5bYG+85V5aqygqUEPg6efpxPJpxMm+KsS7EiDtnK7t/5YZ1FQADYcPdUi9U1jbXeObLCpR6PXQF64XtSC3Mxt3NttQqXd5TmaMAdsqIiM6giF6rJRVqo3ONZ75arG3gxbRwYXZC6MbQanB3nZKoVN2oOQfrKgBmvPw5laXGM2/8XJ1aqVPjrunCKa0WiV4b/+diSK9H4jLcVQWsplqk1muNN0V4ORMGALAOyDwAxAKZB4BYIPMAEAtkHgBigcwDQCyQeQCIBTIPALFA5gEgFsg8AMQCmQeAWHCU+QULf5wxc5IVNiQSVX4e1v7ipXNW2BYAH+DLoRHb/vjVQis3W+YPH9m/fOV8c60NAGAhZsv806ePzLUqAIDlmGd8+9jp49LTUxFCZ8+e/G3L7mZ+AXl5uev/t+LZ88cUCrVxY9/Ro8Z/EtTesPD165d37tr6Mi+Hx+M3ber//ZQfXV0b1nNDOTlZY8YO3fTrzj17tl+7fqlBA5fPu/Ua9+0Uw72uTGw0+cKZ7ds3S6oknTt3Hfrl12+uMzPzwc5dW588yeTxBZ1CuowaOY7DIeiV5zdvXv1f/MrXr0ubNmnWv/+QiC/+GSi6trds4aKfSCRSp5Auv6xZTKFQAvxbLpi/8sjRAzt3beVyeeG9IieM/55EIu0/sHvP3h0zpsetXb9MJKp0d/ccOWJsr159EEJJh/bt2bt9Wuzs+Qtm9e8/ZMrkGRUV5Zs2r83ITFcoFMHBnUaOGOvl9c8dim+lXE9M3PXkaaaTk3NgYJtxY6cIhc4mptfm3Y1qNJo//tx0K+VaaWlxYGDQgH5DQkI+M71RE3XevHn1wsUzDx7el0jEzQMCv/56rOFz+O52tVrtgYN/7dy1FSHUonmr0aPGt2r1zy2bqFTaocOJW35bT6fTAwODZv+0iMc1z9jq5mnn16/d2rx5YK9efS4m323mF1BZWfHdlG9cXBpu/W3Pr/HbBXynxUvmyGQyhNDdeynzFszs1avP/n1/z/95RUlJ0foNK+q/IRqNhhBas3ZJWNgXZ0/fnDt7yf4Duw175iY2mp39YumyuF69IncnHAnvFRm/8ZeaFb4qyJ8xa5JCqdgYv33xwtXZ2c+nTR+n0RBlgOQ33bx59ef5M2LGTF6xfMNnn32+6pdF55NPm37LqFRqRmZ6Rmb6gcRTWzYlZGSmfz/tW51Oe+LY5fnzVuw/sDsl5TpCiEKhSqXVyRdO/5Vw9Mjh5LDu4StWLcjPf2m4t5RMJj127ODsnxYN6DdEq9VO+2F8Wvq9abFz/tyWKOA7TZo8qqDwFULo2fMns+d8/8knwTv+PDh1yqysrGcrVy0wMd2EtzaKENoQv+pg0p4B/Yfu+et4aNew+QtnXb6SbGLlJupUKBRLl8cplcqffly4bOl6b+/Gc+OmVVSUG93u1t/jjx49sGjh6rg5Sxs0cP1x9pS8vFxDkZevnJdKq1euiJ85Y15GRtr27Wa7r65F7mNz4OBfdAZjxg9xhrt/z5wxb/CQ8KPHDnwVPerP7Zu7duk+eNAwhBCPx580cfqMmZOePH0U4N+i/usP7dqjW2gPhFCbNm3d3TyePXvcI+wLExs9euyAq0vDkV+PRQh9EtS+oqL8ftpdw6rOnz9Fo9IWL1zN4/ERQjN++Pmr4VHXrl8yrJ9Qtu/Y0rVL9549IhBCwe1DpNJqmUyKEDL9lqlUqu8mz6DRaDwe39enqUar+Wb0BMP/mc8XZGU/NzSYGo1m4IBoFovFQqzRo8YfOrQv+cKZ0aPGkUgkhUIRHT2q7SfBCKG0tHt5eblrVm82PJ04Ifb6jctJSXumTpmV8TCNyWSOGD6GTCa7ujYM8G+RnfMCIVTbdBPe2qhSqTxz9sSwr0b3jRqEEOod0S8jI31Xwu+hXcNqW/nDh2m11clkMrdt3cdisQyfqOYBgUePHXyYkRbaNeyt7Yol4v0Hdsd+/1Nw+xCEUMeOn8pk0vKKMm/vxgghNpvz9YgYQ8HXb1x+8PC+ud5oi2Q+O+eFn1+AIXsIIQ6H4+XZ6Nmzxwih7OznoV3Dapb0b9YCIfTkSeZ7Zb5Zs+Y1jx0cHKurq0xvtKAgv7FPk5qXBAS0rHmcmZkeENDS8PYghBo2dHN393zw8D7RMq/X67Oyn/foEVEzZcL47w0PTL9lHh5ehs4XQojFZgud/u1Uc9gcw1tjUPOukUgkd3fPvLycmlkB/v+8Iw8z0mg0miEShiWD2rRLf5CKEApsFaRQKGbPjW3frmOnTl09PbwMHebaptepZqPPnj1WqVTB7f+933lQm3anTh8TS8S1rdxEnQghmUy67Y+Naen3ysvLDFNEosp3t5ubk/Xmp5FKpS5a+G8PtFXgv/dl5XH5KqWyPn9UfVgk8xXlZR4e/xn+mcliyeSy6upqpVLJYPw70h6bzTb8j95r/WRjN7qobaMIIYlE7On575DPLOa/I/5XV1c9efro87D/fEoqK8rfqx47oFKpdDrdm2+NQZ1v2VvvhdG3xoDBYPz7mMmUSqtrntLp9P/fXJVarX7r7eDzBQihZn4BK5ZvuHIleevv8Zs2r2vXtsPoUeMDA9vUNr3OP/nNjSKEpnwf89YClRXlta3cRJ0lJcXfTxvb9pMOP89d1qJFKxKJ1DM8xMR2me/8zw1qWi/Dd0qdf079WSTzbA5HofzPeHpymczTw5vJZCKEFAp5zXSpTIoQerNxMPtGEUJcLu/NWW9+xTgJnVu1CjJ0R2vwuPyPr8e20Gg0Mpn8Zg4NzPiWSaXSmoOjSoVCwHd6dxmh0JnFYi1dsu7NiZT/v1VYxw6dO3bo/M3oCffupSQ9o6e0AAAOCklEQVQd2jtnbuyhpHNUKrW26fUsTOjcACH0w/S5b7UZLi4Na9uoiTovXT6nUql++nEhi8V6q4V/C4fj8AEN3sezSOb9m7U4c/aEWq029PokVZKXeTm9evWhUqn+zZpnZj6oWdLw2LeJn+U2ihBydXW7cfOKTqcztEI3b12teVUTX7+z5062ad22poHKzc1+s1NAEGQy2d+/xcOMtJopv2/bqFKpJk+abq637H7anc8+7WbYf87Lz+3Uqcu7yzRp0kwul7u4NPRw9zRMKSwq4PMEhl19pUrZsUNnZ+cG4eGRDRu6x04fV1xSVPa61Oh0T4/63mjE08Pb0Aep2SmorKzQ6/VsNru2jZqoUyIROzpyDYFHCBmOBRrVtKk/lUpNf5DavHmgYfdq9tzYz0N7hodHvue/9v2Y7fy8h4fX48cZqffvVFZWREUNkkqr16xdWlJSnJubvXzFPCaD2TuiP0JoQP+h165fSkraK6mS3E+7u2nz2rafBPs1NcMd5k1stFu3niJRZfzGX/R6/f20u0eO7K951eDBw3U63cZNaxQKRX7+y9+2bhgzdmidB4HsUr+owXfu3Ezcn3A/7e7RYwf37tvp49PEXG8ZmUw+dGhfXl6uVqv9c/tmpVIZ1v2Ldxdr17ZDhw6dV69eXFJSLBaLjhw9MGHi16dPH0MIZWSmL1g46/iJQyJR5aPHGYcO73N2btDQ1a226fWvjc1mjx41flfC7w8fpqlUqstXkmfMmrT+fytMbNREnb6+fuXlZceOJ2k0mpTbN1JTb/N4/NLS4ne36+Dg0LNH76NHD5w6fex+2t34jb/cu5diyL9Fma2dj+oz8NmzxzNnTV65Ir59u47z561ISNgWPSySx+M3bx74v/XbDP26Xr36vC4rTTyQsHHTGlfXhu3bhXw79juzFODp4VXbRoPbh0wY//2xYwe79wh2dW04d/aSqbFjDTft4jpy/9iWuG/fzvETR+Tl5QYEtJw54+dmfgFmKcm2hIdHSqrEO3dtlUqlQqHzuG+n9I7oZ663jEQiDflyxPQZE8rLy1gs1k+zFtSczX7L8qXrjx1PWrRk9qNHD728GvXoETFwYDRCaMiXI0Siyo2/rl67bhmdTu/+efi6tVupVGpt09+rvOihI5s0abZn347U1NscjkPLFq1/+CHOxEZN1BnWPfzly+xdCb+vW788uH3Ij7MW7EvctWfvjqoqyZvHng2+n/rj+v+tWLN2qVarbdqk2aIFvxgO2luU8fvV3T5ToVKgNt2M7HGBt5QVKlNOlkbPwNct60rzlcn7SiPH4aKqpEP7Nm1em3zuNtaFEMiFvYVtuvAatzTy6zIcXWMDALACixzD+xh79u7Yu3eH0VmNGvtu3PCn1SsCtgc+RSbgLvNRUYM+/7yX0VlUCu6qBfUxaGD0oIHR1twifIpMwN3f7+jg6OjgiHUVwLbBp8gE2J8HgFgg8wAQC2QeAGKBzANALJB5AIgFMg8AsUDmASAWyDwAxAKZB4BYjP8Oj84k6ZA5h+OxY2QSErjQsK7iXXqBCx3rGgBmOHwamWI8wsbbeUcB7fVLudFZ4C3lRUoqDXffj0I3RvbDqnosCOxT3uNqp4bGv/SNZ97Fi2HWUffsmVSi9mjKqseCVkWhknwCHUSvzTZYKrAh8mqNswfDgW+8F19rO+/RlHklyciAPuBNz+9LygsUAcFcrAsxIqS3U/JfRVhXATBwfndhcE9BbXONj5NjkHlT/Dytuk2oUOBKp1DhaN9/VJYqC7NkpXnyqG/dzDsUsRlVlqqS4l+FDm7Ic6azHHB3DSUwL4VMKylTXT9a+sVIVxdv40No15F5hFBOpjTtsqg4R0HB3y4rhvgN6BqVzj/YsV33Wr9NcUIq0aScqsjJkPIb0MqLVViXYz1arY5CIVBDxRPSJBXqxi047XsKTB++rSPzNZRynfnKs3kUGolKtbEvQYVMh9fuiEVEREQkJSUZ7sBBBHodYnLq9R1X3/4eg0Wgr0y7xGQT6x1Ua2UMFhk+t++C/wgAxAKZB4BYIPMAEAtkHgBigcwDQCyQeQCIBTIPALFA5gEgFsg8AMQCmQeAWCDzABALZB4AYoHMA0AskHkAiAUyDwCxQOYBIBbIPADEApkHgFgg8wAQC2QeAGKBzANALJB5AIgFMg/sU+vWrXF7fyFsQeaBfXrw4EE979dCNJB5AIgFMg8AsUDmASAWyDwAxAKZB4BYIPMAEAtkHgBigcwDQCyQeQCIBTIPALFA5gEgFsg8AMQCmQeAWCDzABALZB4AYoHMA0AsJBhXANiTtm3bGh4YBsnR6/VkMnncuHHjxo3DujS8gHYe2BU/Pz+EEJlMJpFIJBKJTCb7+PgMGzYM67pwBDIP7Ep0dDSLxap5SqVSIyMjHRwcMC0KXyDzwK4MGDDAy8ur5qmnp+fgwYMxrQh3IPPA3gwdOpTBYCCEKBRK3759ORwO1hXhC2Qe2JsBAwb4+PgghLy8vKCRfxdkHtihoUOHslisyMhINpuNdS24A+fqAGZUSl1OhrTghbK8WCmv0tIYZHG5ylwr16g1VBrVXGsTuDAUUg3LgerUkO7mw2jSisPkUMy1ciuDzAMMvHwsTbssKcySOTZgO7qwKVQKlU6hMqg4vvGMXq3UapRanUZbVSavei0TujM+CeU1DbK9MwKQeWBVRTnyy4fKVUqSsBGP48SqxytwSipSVOaJSXpt1wFCL39b2oOAzAMr0evRpUMVBVkKgQfXptP+JplYWf5S5OJB7zXMmWQjB8cg88BKjv1erFBQXJo6YV2I+ZXlipBaMXiqB9aF1AtkHljDmd2vpXKqkycX60IsRVwq1ctl/Sc0xLqQutlIdwTYspN/FsvsOvAIIZ4Lh8xkH9xQgHUhdYPMA8u6faZSKqUI7DrwBlxXDonBvJRUhnUhdYDMAwt6/UrxLE1ql/vwRgm9+cUvVfnPZFgXYgpkHljQlSPlPHce1lVYFc+df+VQOdZVmAKZB5ZS8EIulegdnW3p3PXHY/EYiEx5nlaNdSG1gswDS7l/WSTwwm8jn3R81S/xX1lizQJvXvoVsSXWbBaQeWARer0+N0NKtEbegM1jlhcp5dVarAsxDjIPLCInQ8p3I2LgDbgu7OwMnHbvzXbhEQBvKslTcIQWzPyd1BM37xwuKnnh5to0qFWPLp2iDYNezl8eHh42TioTnb2wjUFn+fuF9IuYzuU6I4SUStlfB+e9yL7r5tq0U/BAy9WGEOI4sUvylC1DLLqRDwTtPLCI8iI1mWKpT1dq+pnEw4s93f3nTD8c0XPilRv7jv69zjCLQqFdurabRCIvmn121tT9OS/Tz1z83TBr/5GlZeX540dvHPXVyuLS7CfPrluoPIQQhUYpK1Babv0fAzIPLEIq1lLplrrC/Pa9o76NPhkYNcvRwcnPt3142LjrKQeqqisMc52dPHuEfsNiOXK5zv5NQ14VPEEIiSWv0zPOf/7Z1428ArmOwsjw72hUpoXKQwhR6RRZFezPAyKhMsg0pkUyr9PpcvIeNPPrWDPFz7e9Xq/LyU0zPPX0aF4zi8XiKpTVCKGKygKEkKuLT80srzcWMzsqk8Jg4zRcsD8PLEIh1bJVOmSBS2Y1GpVWqz59fsvp81venF4lrfj/h0ZG3pDKxAghBv3fQwx0ugWv59WpdTKxxnLr/xiQeWARbEeKWqW1RKrodCaDzm4X1Lt1y+5vThc6mbqUlcPmIYRUakXNFIVSaoHq/qFWalmOOA0XTssCts6BT62SWqqhc3drJldUNfVtZ3iq0ajLKwv4PFcTLxHw3RFCuXkPDF16jUb9POs2hyOwUIUapZbDw+mAeTjd5QC2zq0xQ1VttgEt39K758SMx5dT7h3T6XQ5L9N275/72/bJGo2pzfF5Lo2925y5sLX09Uu1WvnXgZ+RJQffU1Qp3H0seIzwY0DmgUX4BHIkry11eZlPo6BpE3fl5KYtWPnFbzumyBXV3wz/hUZjmH7VV4Pme3u2XL955Nwln7NZ3A5t+yKLDRgjLZP5tsLpvTRgnBxgKXtW5vMbCdm8OqJof1Qy9asHxWMWNsa6EOOgnQeWEvgpV1JqweNkuCUukbb6FL8XF8ExPGAprT/j3Tmbq/Lk0lnGP2bXbx04lbzF6Cy1WllbXz164LzA5qHmKjLnZdofu38wOkujUVEoNJKx3f7oAfMCWxivQafRleWIvpzUxFwVmh307YEFPUutupNc7RHoYnSuXFEtl0uMzpLKJBy28eG0HDhOdLo5D49VVBYana5QVDOZxm9ZweEIGLWc3i9+Wtb8E0abUL4ZKzQvyDywrBPbihGT42DJ623wQy5WysoqB32H60GvYX8eWFbk2IYlT8vUCpz+KM2MdFpdzt0inAceMg+s4eu4RkWPSrQaHdaFWFbBg+KRcY2wrqJukHlgcXQGOXqG57OreTKRoh6L2x5FtSrjXM6gKW4OfBs4KA7788B69q7OZ3A5TjgeJO8DVLySVJdIRszxJpPxe1fdN0HmgVWlnK5ITa509XNy8rL5u1xUFlSVvqhoEcLt0t8Z61reA2QeWJtaqbtyuDzvqYzGojs4sx0bsChUnF6O8i6tRltdrqgukykkCvcmrG6DnFkONlO8AWQeYEOt1OVkSp+mSqvF2soiBZ1FcRQyVXKcHt5ncKiS1wqVXMt3YXB4FP+2nMYtOUy2jaXdADIPsKdR62QSrbRKq9Pg9NNIpiC2I5XNpdDoNn/YGzIPALHY/JcWAOC9QOYBIBbIPADEApkHgFgg8wAQC2QeAGL5P9jo7DE67WPvAAAAAElFTkSuQmCC",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import Image, display\n",
    "from deep_research_from_scratch.research_agent_mcp import agent_mcp\n",
    "\n",
    "# Show the agent\n",
    "display(Image(agent_mcp.get_graph(xray=True).draw_mermaid_png()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #000080; text-decoration-color: #000080\">╭─────────────────────────────────────────────────── 🧑 Human ────────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> I want to identify and evaluate the coffee shops in San Francisco that are considered the best based            <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> specifically                                                                                                    <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> on coffee quality. My research should focus on analyzing and comparing coffee shops within the San Francisco    <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> area,                                                                                                           <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> using coffee quality as the primary criterion. I am open regarding methods of assessing coffee quality (e.g.,   <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> expert reviews, customer ratings, specialty coffee certifications), and there are no constraints on ambiance,   <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> location, wifi, or food options unless they directly impact perceived coffee quality. Please prioritize primary <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> sources such as the official websites of coffee shops, reputable third-party coffee review organizations (like  <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> Coffee Review or Specialty Coffee Association), and prominent review aggregators like Google or Yelp where      <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> direct                                                                                                          <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> customer feedback about coffee quality can be found. The study should result in a well-supported list or        <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> ranking of                                                                                                      <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> the top coffee shops in San Francisco, emphasizing their coffee quality according to the latest available data  <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> as                                                                                                              <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">│</span> of July 2025..                                                                                                  <span style=\"color: #000080; text-decoration-color: #000080\">│</span>\n",
       "<span style=\"color: #000080; text-decoration-color: #000080\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[34m╭─\u001b[0m\u001b[34m──────────────────────────────────────────────────\u001b[0m\u001b[34m 🧑 Human \u001b[0m\u001b[34m───────────────────────────────────────────────────\u001b[0m\u001b[34m─╮\u001b[0m\n",
       "\u001b[34m│\u001b[0m I want to identify and evaluate the coffee shops in San Francisco that are considered the best based            \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m specifically                                                                                                    \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m on coffee quality. My research should focus on analyzing and comparing coffee shops within the San Francisco    \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m area,                                                                                                           \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m using coffee quality as the primary criterion. I am open regarding methods of assessing coffee quality (e.g.,   \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m expert reviews, customer ratings, specialty coffee certifications), and there are no constraints on ambiance,   \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m location, wifi, or food options unless they directly impact perceived coffee quality. Please prioritize primary \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m sources such as the official websites of coffee shops, reputable third-party coffee review organizations (like  \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m Coffee Review or Specialty Coffee Association), and prominent review aggregators like Google or Yelp where      \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m direct                                                                                                          \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m customer feedback about coffee quality can be found. The study should result in a well-supported list or        \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m ranking of                                                                                                      \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m the top coffee shops in San Francisco, emphasizing their coffee quality according to the latest available data  \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m as                                                                                                              \u001b[34m│\u001b[0m\n",
       "\u001b[34m│\u001b[0m of July 2025..                                                                                                  \u001b[34m│\u001b[0m\n",
       "\u001b[34m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╭───────────────────────────────────────────────────── 📝 AI ─────────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> I'll help you research the best coffee shops in San Francisco based on coffee quality. Let me start by          <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> exploring what files are available and then systematically gather information from relevant sources.            <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 🔧 Tool Call: list_allowed_directories                                                                          <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    Args: {}                                                                                                     <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    ID: toolu_01N2uzUh8pGoXiPGhMJUGCix                                                                           <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[37m╭─\u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m 📝 AI \u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m─╮\u001b[0m\n",
       "\u001b[37m│\u001b[0m I'll help you research the best coffee shops in San Francisco based on coffee quality. Let me start by          \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m exploring what files are available and then systematically gather information from relevant sources.            \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 🔧 Tool Call: list_allowed_directories                                                                          \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    Args: {}                                                                                                     \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    ID: toolu_01N2uzUh8pGoXiPGhMJUGCix                                                                           \u001b[37m│\u001b[0m\n",
       "\u001b[37m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
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     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #808000; text-decoration-color: #808000\">╭──────────────────────────────────────────────── 🔧 Tool Output ─────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> Allowed directories:                                                                                            <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> /Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files                         <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[33m╭─\u001b[0m\u001b[33m───────────────────────────────────────────────\u001b[0m\u001b[33m 🔧 Tool Output \u001b[0m\u001b[33m────────────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m\n",
       "\u001b[33m│\u001b[0m Allowed directories:                                                                                            \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m /Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files                         \u001b[33m│\u001b[0m\n",
       "\u001b[33m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╭───────────────────────────────────────────────────── 📝 AI ─────────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 🔧 Tool Call: list_directory                                                                                    <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    Args: {                                                                                                      <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>   \"path\": \"/Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files\"             <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> }                                                                                                               <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    ID: toolu_01VdAt2acQYhpsserL5qid7S                                                                           <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[37m╭─\u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m 📝 AI \u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m─╮\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 🔧 Tool Call: list_directory                                                                                    \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    Args: {                                                                                                      \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m   \"path\": \"/Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files\"             \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m }                                                                                                               \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    ID: toolu_01VdAt2acQYhpsserL5qid7S                                                                           \u001b[37m│\u001b[0m\n",
       "\u001b[37m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #808000; text-decoration-color: #808000\">╭──────────────────────────────────────────────── 🔧 Tool Output ─────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> [FILE] coffee_shops_sf.md                                                                                       <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[33m╭─\u001b[0m\u001b[33m───────────────────────────────────────────────\u001b[0m\u001b[33m 🔧 Tool Output \u001b[0m\u001b[33m────────────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m\n",
       "\u001b[33m│\u001b[0m [FILE] coffee_shops_sf.md                                                                                       \u001b[33m│\u001b[0m\n",
       "\u001b[33m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╭───────────────────────────────────────────────────── 📝 AI ─────────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> Perfect! I found a file specifically about San Francisco coffee shops. Let me read this to see what information <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> is available.                                                                                                   <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 🔧 Tool Call: read_text_file                                                                                    <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    Args: {                                                                                                      <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>   \"path\":                                                                                                       <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> \"/Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files/coffee_shops_sf.md\"    <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> }                                                                                                               <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    ID: toolu_01Eu5rUQNPhHuDesAF6G4Crp                                                                           <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[37m╭─\u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m 📝 AI \u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m─╮\u001b[0m\n",
       "\u001b[37m│\u001b[0m Perfect! I found a file specifically about San Francisco coffee shops. Let me read this to see what information \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m is available.                                                                                                   \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 🔧 Tool Call: read_text_file                                                                                    \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    Args: {                                                                                                      \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m   \"path\":                                                                                                       \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m \"/Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files/coffee_shops_sf.md\"    \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m }                                                                                                               \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    ID: toolu_01Eu5rUQNPhHuDesAF6G4Crp                                                                           \u001b[37m│\u001b[0m\n",
       "\u001b[37m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #808000; text-decoration-color: #808000\">╭──────────────────────────────────────────────── 🔧 Tool Output ─────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> # San Francisco Coffee Shops Research                                                                           <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span>                                                                                                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> ## Top Coffee Shops in San Francisco                                                                            <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span>                                                                                                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> ### Blue Bottle Coffee                                                                                          <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Founded**: 2002 in Oakland, expanded to SF                                                                  <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Specialty**: Single-origin coffee, pour-over methods                                                        <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Notable**: Known for freshly roasted beans, minimalist aesthetic                                            <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Locations**: Multiple SF locations including Ferry Building                                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span>                                                                                                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> ### Philz Coffee                                                                                                <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Founded**: 2003 in San Francisco                                                                            <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Specialty**: Custom blended coffee, personalized service                                                    <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Notable**: Founded by Phil Jaber, known for unique blends like \"Tesora\"                                     <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Locations**: Original location in Mission District, now citywide                                            <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span>                                                                                                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> ### Sightglass Coffee                                                                                           <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Founded**: 2009                                                                                             <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Specialty**: Third-wave coffee, roasting transparency                                                       <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Notable**: Large roastery with viewing windows, industrial aesthetic                                        <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Location**: SOMA district flagship location                                                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span>                                                                                                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> ### Ritual Coffee Roasters                                                                                      <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Founded**: 2005                                                                                             <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Specialty**: Direct trade relationships, seasonal offerings                                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Notable**: Pioneer in San Francisco's third-wave coffee movement                                            <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Locations**: Multiple locations including Castro and Mission                                                <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span>                                                                                                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> ### Four Barrel Coffee                                                                                          <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Founded**: 2008                                                                                             <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Specialty**: Small-batch roasting, community focus                                                          <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Notable**: Known for Valencia Street location, local institution                                            <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - **Location**: Mission District                                                                                <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[33m╭─\u001b[0m\u001b[33m───────────────────────────────────────────────\u001b[0m\u001b[33m 🔧 Tool Output \u001b[0m\u001b[33m────────────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m\n",
       "\u001b[33m│\u001b[0m # San Francisco Coffee Shops Research                                                                           \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m                                                                                                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m ## Top Coffee Shops in San Francisco                                                                            \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m                                                                                                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m ### Blue Bottle Coffee                                                                                          \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Founded**: 2002 in Oakland, expanded to SF                                                                  \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Specialty**: Single-origin coffee, pour-over methods                                                        \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Notable**: Known for freshly roasted beans, minimalist aesthetic                                            \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Locations**: Multiple SF locations including Ferry Building                                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m                                                                                                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m ### Philz Coffee                                                                                                \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Founded**: 2003 in San Francisco                                                                            \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Specialty**: Custom blended coffee, personalized service                                                    \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Notable**: Founded by Phil Jaber, known for unique blends like \"Tesora\"                                     \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Locations**: Original location in Mission District, now citywide                                            \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m                                                                                                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m ### Sightglass Coffee                                                                                           \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Founded**: 2009                                                                                             \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Specialty**: Third-wave coffee, roasting transparency                                                       \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Notable**: Large roastery with viewing windows, industrial aesthetic                                        \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Location**: SOMA district flagship location                                                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m                                                                                                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m ### Ritual Coffee Roasters                                                                                      \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Founded**: 2005                                                                                             \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Specialty**: Direct trade relationships, seasonal offerings                                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Notable**: Pioneer in San Francisco's third-wave coffee movement                                            \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Locations**: Multiple locations including Castro and Mission                                                \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m                                                                                                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m ### Four Barrel Coffee                                                                                          \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Founded**: 2008                                                                                             \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Specialty**: Small-batch roasting, community focus                                                          \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Notable**: Known for Valencia Street location, local institution                                            \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - **Location**: Mission District                                                                                \u001b[33m│\u001b[0m\n",
       "\u001b[33m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╭───────────────────────────────────────────────────── 📝 AI ─────────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> Let me search for any additional files that might contain more detailed information about coffee quality        <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> assessments, reviews, or rankings.                                                                              <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 🔧 Tool Call: search_files                                                                                      <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    Args: {                                                                                                      <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>   \"path\": \"/Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files\",            <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>   \"pattern\": \"coffee quality\"                                                                                   <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> }                                                                                                               <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    ID: toolu_016Y544VSWkLugdxGawQ465U                                                                           <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[37m╭─\u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m 📝 AI \u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m─╮\u001b[0m\n",
       "\u001b[37m│\u001b[0m Let me search for any additional files that might contain more detailed information about coffee quality        \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m assessments, reviews, or rankings.                                                                              \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 🔧 Tool Call: search_files                                                                                      \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    Args: {                                                                                                      \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m   \"path\": \"/Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files\",            \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m   \"pattern\": \"coffee quality\"                                                                                   \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m }                                                                                                               \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    ID: toolu_016Y544VSWkLugdxGawQ465U                                                                           \u001b[37m│\u001b[0m\n",
       "\u001b[37m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #808000; text-decoration-color: #808000\">╭──────────────────────────────────────────────── 🔧 Tool Output ─────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> No matches found                                                                                                <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[33m╭─\u001b[0m\u001b[33m───────────────────────────────────────────────\u001b[0m\u001b[33m 🔧 Tool Output \u001b[0m\u001b[33m────────────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m\n",
       "\u001b[33m│\u001b[0m No matches found                                                                                                \u001b[33m│\u001b[0m\n",
       "\u001b[33m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
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     "output_type": "display_data"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╭───────────────────────────────────────────────────── 📝 AI ─────────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 🔧 Tool Call: search_files                                                                                      <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    Args: {                                                                                                      <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>   \"path\": \"/Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files\",            <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>   \"pattern\": \"review\"                                                                                           <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> }                                                                                                               <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    ID: toolu_01VuBxp2GA3kMVdnYhWiJXAX                                                                           <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[37m╭─\u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m 📝 AI \u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m─╮\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 🔧 Tool Call: search_files                                                                                      \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    Args: {                                                                                                      \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m   \"path\": \"/Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files\",            \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m   \"pattern\": \"review\"                                                                                           \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m }                                                                                                               \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    ID: toolu_01VuBxp2GA3kMVdnYhWiJXAX                                                                           \u001b[37m│\u001b[0m\n",
       "\u001b[37m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #808000; text-decoration-color: #808000\">╭──────────────────────────────────────────────── 🔧 Tool Output ─────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> No matches found                                                                                                <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[33m╭─\u001b[0m\u001b[33m───────────────────────────────────────────────\u001b[0m\u001b[33m 🔧 Tool Output \u001b[0m\u001b[33m────────────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m\n",
       "\u001b[33m│\u001b[0m No matches found                                                                                                \u001b[33m│\u001b[0m\n",
       "\u001b[33m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
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     "output_type": "display_data"
    },
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     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╭───────────────────────────────────────────────────── 📝 AI ─────────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 🔧 Tool Call: search_files                                                                                      <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    Args: {                                                                                                      <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>   \"path\": \"/Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files\",            <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>   \"pattern\": \"rating\"                                                                                           <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> }                                                                                                               <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    ID: toolu_01APLzfnn48yqFL9pmywn5L3                                                                           <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[37m╭─\u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m 📝 AI \u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m─╮\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 🔧 Tool Call: search_files                                                                                      \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    Args: {                                                                                                      \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m   \"path\": \"/Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files\",            \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m   \"pattern\": \"rating\"                                                                                           \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m }                                                                                                               \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    ID: toolu_01APLzfnn48yqFL9pmywn5L3                                                                           \u001b[37m│\u001b[0m\n",
       "\u001b[37m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #808000; text-decoration-color: #808000\">╭──────────────────────────────────────────────── 🔧 Tool Output ─────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> No matches found                                                                                                <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[33m╭─\u001b[0m\u001b[33m───────────────────────────────────────────────\u001b[0m\u001b[33m 🔧 Tool Output \u001b[0m\u001b[33m────────────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m\n",
       "\u001b[33m│\u001b[0m No matches found                                                                                                \u001b[33m│\u001b[0m\n",
       "\u001b[33m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╭───────────────────────────────────────────────────── 📝 AI ─────────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 🔧 Tool Call: think_tool                                                                                        <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    Args: {                                                                                                      <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>   \"reflection\": \"I've found one primary file about San Francisco coffee shops, which provides basic information <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> about 5 notable coffee establishments: Blue Bottle Coffee, Philz Coffee, Sightglass Coffee, Ritual Coffee       <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> Roasters, and Four Barrel Coffee. \\n\\nHowever, the current information is quite limited for the user's specific <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> request. The file provides:\\n- Basic founding information and specialties\\n- General descriptions of each       <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> shop's focus\\n- Location information\\n\\nWhat's missing for a comprehensive coffee quality analysis:\\n- Specific <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> quality assessments or ratings\\n- Expert reviews or certifications\\n- Customer feedback about coffee quality\\n- <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> Comparative rankings based on coffee quality\\n- Third-party review data from sources like Coffee Review, SCA,   <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> Google, or Yelp\\n- Current/recent data (the user specifically requested data as of July 2025)\\n\\nThe            <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> information I have is quite basic and doesn't meet the user's specific criteria for evaluating coffee quality.  <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> I should check if there are any other files that might contain more detailed quality assessments, reviews, or   <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> ratings data. Let me do one more comprehensive search to see if there are any additional relevant files.\"       <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> }                                                                                                               <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    ID: toolu_01M4zyGeTTAGxcRikSvKaeu4                                                                           <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[37m╭─\u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m 📝 AI \u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m─╮\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 🔧 Tool Call: think_tool                                                                                        \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    Args: {                                                                                                      \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m   \"reflection\": \"I've found one primary file about San Francisco coffee shops, which provides basic information \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m about 5 notable coffee establishments: Blue Bottle Coffee, Philz Coffee, Sightglass Coffee, Ritual Coffee       \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m Roasters, and Four Barrel Coffee. \\n\\nHowever, the current information is quite limited for the user's specific \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m request. The file provides:\\n- Basic founding information and specialties\\n- General descriptions of each       \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m shop's focus\\n- Location information\\n\\nWhat's missing for a comprehensive coffee quality analysis:\\n- Specific \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m quality assessments or ratings\\n- Expert reviews or certifications\\n- Customer feedback about coffee quality\\n- \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m Comparative rankings based on coffee quality\\n- Third-party review data from sources like Coffee Review, SCA,   \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m Google, or Yelp\\n- Current/recent data (the user specifically requested data as of July 2025)\\n\\nThe            \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m information I have is quite basic and doesn't meet the user's specific criteria for evaluating coffee quality.  \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m I should check if there are any other files that might contain more detailed quality assessments, reviews, or   \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m ratings data. Let me do one more comprehensive search to see if there are any additional relevant files.\"       \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m }                                                                                                               \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    ID: toolu_01M4zyGeTTAGxcRikSvKaeu4                                                                           \u001b[37m│\u001b[0m\n",
       "\u001b[37m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #808000; text-decoration-color: #808000\">╭──────────────────────────────────────────────── 🔧 Tool Output ─────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> Reflection recorded: I've found one primary file about San Francisco coffee shops, which provides basic         <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> information about 5 notable coffee establishments: Blue Bottle Coffee, Philz Coffee, Sightglass Coffee, Ritual  <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> Coffee Roasters, and Four Barrel Coffee.                                                                        <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span>                                                                                                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> However, the current information is quite limited for the user's specific request. The file provides:           <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - Basic founding information and specialties                                                                    <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - General descriptions of each shop's focus                                                                     <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - Location information                                                                                          <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span>                                                                                                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> What's missing for a comprehensive coffee quality analysis:                                                     <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - Specific quality assessments or ratings                                                                       <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - Expert reviews or certifications                                                                              <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - Customer feedback about coffee quality                                                                        <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - Comparative rankings based on coffee quality                                                                  <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - Third-party review data from sources like Coffee Review, SCA, Google, or Yelp                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> - Current/recent data (the user specifically requested data as of July 2025)                                    <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span>                                                                                                                 <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> The information I have is quite basic and doesn't meet the user's specific criteria for evaluating coffee       <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> quality. I should check if there are any other files that might contain more detailed quality assessments,      <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> reviews, or ratings data. Let me do one more comprehensive search to see if there are any additional relevant   <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> files.                                                                                                          <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
       "<span style=\"color: #808000; text-decoration-color: #808000\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[33m╭─\u001b[0m\u001b[33m───────────────────────────────────────────────\u001b[0m\u001b[33m 🔧 Tool Output \u001b[0m\u001b[33m────────────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m\n",
       "\u001b[33m│\u001b[0m Reflection recorded: I've found one primary file about San Francisco coffee shops, which provides basic         \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m information about 5 notable coffee establishments: Blue Bottle Coffee, Philz Coffee, Sightglass Coffee, Ritual  \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m Coffee Roasters, and Four Barrel Coffee.                                                                        \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m                                                                                                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m However, the current information is quite limited for the user's specific request. The file provides:           \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - Basic founding information and specialties                                                                    \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - General descriptions of each shop's focus                                                                     \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - Location information                                                                                          \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m                                                                                                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m What's missing for a comprehensive coffee quality analysis:                                                     \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - Specific quality assessments or ratings                                                                       \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - Expert reviews or certifications                                                                              \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - Customer feedback about coffee quality                                                                        \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - Comparative rankings based on coffee quality                                                                  \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - Third-party review data from sources like Coffee Review, SCA, Google, or Yelp                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m - Current/recent data (the user specifically requested data as of July 2025)                                    \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m                                                                                                                 \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m The information I have is quite basic and doesn't meet the user's specific criteria for evaluating coffee       \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m quality. I should check if there are any other files that might contain more detailed quality assessments,      \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m reviews, or ratings data. Let me do one more comprehensive search to see if there are any additional relevant   \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m files.                                                                                                          \u001b[33m│\u001b[0m\n",
       "\u001b[33m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╭───────────────────────────────────────────────────── 📝 AI ─────────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 🔧 Tool Call: directory_tree                                                                                    <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    Args: {                                                                                                      <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>   \"path\": \"/Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files\"             <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> }                                                                                                               <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>    ID: toolu_012v1q7GnaVfKjZEvK8tEpU7                                                                           <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
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       "\u001b[37m╭─\u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m 📝 AI \u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m─╮\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 🔧 Tool Call: directory_tree                                                                                    \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    Args: {                                                                                                      \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m   \"path\": \"/Users/rlm/Desktop/Code/deep_research_from_scratch/src/deep_research_from_scratch/files\"             \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m }                                                                                                               \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m    ID: toolu_012v1q7GnaVfKjZEvK8tEpU7                                                                           \u001b[37m│\u001b[0m\n",
       "\u001b[37m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
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       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> [                                                                                                               <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
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       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span>     \"name\": \"coffee_shops_sf.md\",                                                                               <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
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       "<span style=\"color: #808000; text-decoration-color: #808000\">│</span> ]                                                                                                               <span style=\"color: #808000; text-decoration-color: #808000\">│</span>\n",
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       "\u001b[33m╭─\u001b[0m\u001b[33m───────────────────────────────────────────────\u001b[0m\u001b[33m 🔧 Tool Output \u001b[0m\u001b[33m────────────────────────────────────────────────\u001b[0m\u001b[33m─╮\u001b[0m\n",
       "\u001b[33m│\u001b[0m [                                                                                                               \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m   {                                                                                                             \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m     \"name\": \"coffee_shops_sf.md\",                                                                               \u001b[33m│\u001b[0m\n",
       "\u001b[33m│\u001b[0m     \"type\": \"file\"                                                                                              \u001b[33m│\u001b[0m\n",
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       "\u001b[33m│\u001b[0m ]                                                                                                               \u001b[33m│\u001b[0m\n",
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      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╭───────────────────────────────────────────────────── 📝 AI ─────────────────────────────────────────────────────╮</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> Based on my research of the available files, I found limited information that doesn't fully meet your specific  <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> requirements for evaluating San Francisco coffee shops based on coffee quality. Here's what I discovered:       <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> ## Available Information from Local Files                                                                       <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> I found one relevant file (`coffee_shops_sf.md`) containing basic information about 5 notable San Francisco     <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> coffee shops:                                                                                                   <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> ### 1. **Blue Bottle Coffee** (Founded 2002)                                                                    <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Coffee Quality Focus**: Single-origin coffee, pour-over methods                                             <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Notable Quality Features**: Known for freshly roasted beans                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Locations**: Multiple SF locations including Ferry Building                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> ### 2. **Philz Coffee** (Founded 2003)                                                                          <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Coffee Quality Focus**: Custom blended coffee, personalized service                                         <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Notable Quality Features**: Unique proprietary blends like \"Tesora\"                                         <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Origin**: Founded in San Francisco (Mission District)                                                       <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> ### 3. **Sightglass Coffee** (Founded 2009)                                                                     <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Coffee Quality Focus**: Third-wave coffee movement, roasting transparency                                   <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Notable Quality Features**: Large roastery with viewing windows for transparency                            <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Location**: SOMA district flagship                                                                          <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> ### 4. **Ritual Coffee Roasters** (Founded 2005)                                                                <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Coffee Quality Focus**: Direct trade relationships, seasonal offerings                                      <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Notable Quality Features**: Pioneer in SF's third-wave coffee movement                                      <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Locations**: Multiple locations (Castro, Mission)                                                           <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> ### 5. **Four Barrel Coffee** (Founded 2008)                                                                    <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Coffee Quality Focus**: Small-batch roasting, community focus                                               <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Notable Quality Features**: Known for artisanal approach                                                    <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - **Location**: Mission District                                                                                <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> ## Research Limitations                                                                                         <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> Unfortunately, the available local files lack the specific quality-focused data you requested:                  <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> **Missing Information:**                                                                                        <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - Expert reviews from Coffee Review or Specialty Coffee Association                                             <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - Customer ratings and quality-specific feedback from Google/Yelp                                               <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - Specialty coffee certifications                                                                               <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - Comparative quality rankings                                                                                  <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - Current data as of July 2025                                                                                  <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> - Detailed quality assessments or scoring systems                                                               <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> **Recommendation:**                                                                                             <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> To complete your research according to your specifications, you would need access to:                           <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 1. Current reviews from Coffee Review or SCA databases                                                          <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 2. Recent Google/Yelp reviews focusing on coffee quality                                                        <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 3. Official websites of these coffee shops for current offerings                                                <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 4. Specialty coffee certification databases                                                                     <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> 5. Recent coffee industry publications or rankings                                                              <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>                                                                                                                 <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> The shops identified above represent San Francisco's prominent third-wave coffee establishments, but a          <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> comprehensive quality-based ranking would require the additional sources you mentioned in your research         <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span> criteria.                                                                                                       <span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">│</span>\n",
       "<span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0\">╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[37m╭─\u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m 📝 AI \u001b[0m\u001b[37m────────────────────────────────────────────────────\u001b[0m\u001b[37m─╮\u001b[0m\n",
       "\u001b[37m│\u001b[0m Based on my research of the available files, I found limited information that doesn't fully meet your specific  \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m requirements for evaluating San Francisco coffee shops based on coffee quality. Here's what I discovered:       \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m ## Available Information from Local Files                                                                       \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m I found one relevant file (`coffee_shops_sf.md`) containing basic information about 5 notable San Francisco     \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m coffee shops:                                                                                                   \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m ### 1. **Blue Bottle Coffee** (Founded 2002)                                                                    \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Coffee Quality Focus**: Single-origin coffee, pour-over methods                                             \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Notable Quality Features**: Known for freshly roasted beans                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Locations**: Multiple SF locations including Ferry Building                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m ### 2. **Philz Coffee** (Founded 2003)                                                                          \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Coffee Quality Focus**: Custom blended coffee, personalized service                                         \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Notable Quality Features**: Unique proprietary blends like \"Tesora\"                                         \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Origin**: Founded in San Francisco (Mission District)                                                       \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m ### 3. **Sightglass Coffee** (Founded 2009)                                                                     \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Coffee Quality Focus**: Third-wave coffee movement, roasting transparency                                   \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Notable Quality Features**: Large roastery with viewing windows for transparency                            \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Location**: SOMA district flagship                                                                          \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m ### 4. **Ritual Coffee Roasters** (Founded 2005)                                                                \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Coffee Quality Focus**: Direct trade relationships, seasonal offerings                                      \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Notable Quality Features**: Pioneer in SF's third-wave coffee movement                                      \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Locations**: Multiple locations (Castro, Mission)                                                           \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m ### 5. **Four Barrel Coffee** (Founded 2008)                                                                    \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Coffee Quality Focus**: Small-batch roasting, community focus                                               \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Notable Quality Features**: Known for artisanal approach                                                    \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - **Location**: Mission District                                                                                \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m ## Research Limitations                                                                                         \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m Unfortunately, the available local files lack the specific quality-focused data you requested:                  \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m **Missing Information:**                                                                                        \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - Expert reviews from Coffee Review or Specialty Coffee Association                                             \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - Customer ratings and quality-specific feedback from Google/Yelp                                               \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - Specialty coffee certifications                                                                               \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - Comparative quality rankings                                                                                  \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - Current data as of July 2025                                                                                  \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m - Detailed quality assessments or scoring systems                                                               \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m **Recommendation:**                                                                                             \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m To complete your research according to your specifications, you would need access to:                           \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 1. Current reviews from Coffee Review or SCA databases                                                          \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 2. Recent Google/Yelp reviews focusing on coffee quality                                                        \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 3. Official websites of these coffee shops for current offerings                                                \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 4. Specialty coffee certification databases                                                                     \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m 5. Recent coffee industry publications or rankings                                                              \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m                                                                                                                 \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m The shops identified above represent San Francisco's prominent third-wave coffee establishments, but a          \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m comprehensive quality-based ranking would require the additional sources you mentioned in your research         \u001b[37m│\u001b[0m\n",
       "\u001b[37m│\u001b[0m criteria.                                                                                                       \u001b[37m│\u001b[0m\n",
       "\u001b[37m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Run the agent\n",
    "from utils import format_messages\n",
    "from langchain_core.messages import HumanMessage\n",
    "\n",
    "research_brief = \"\"\"I want to identify and evaluate the coffee shops in San Francisco that are considered the best based specifically  \n",
    "on coffee quality. My research should focus on analyzing and comparing coffee shops within the San Francisco area, \n",
    "using coffee quality as the primary criterion. I am open regarding methods of assessing coffee quality (e.g.,      \n",
    "expert reviews, customer ratings, specialty coffee certifications), and there are no constraints on ambiance,      \n",
    "location, wifi, or food options unless they directly impact perceived coffee quality. Please prioritize primary    \n",
    "sources such as the official websites of coffee shops, reputable third-party coffee review organizations (like     \n",
    "Coffee Review or Specialty Coffee Association), and prominent review aggregators like Google or Yelp where direct  \n",
    "customer feedback about coffee quality can be found. The study should result in a well-supported list or ranking of\n",
    "the top coffee shops in San Francisco, emphasizing their coffee quality according to the latest available data as  \n",
    "of July 2025.\"\"\"\n",
    "\n",
    "result = await agent_mcp.ainvoke({\"researcher_messages\": [HumanMessage(content=f\"{research_brief}.\")]})\n",
    "format_messages(result['researcher_messages'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see the trace [here](https://smith.langchain.com/public/3090174a-8ba2-4dec-9584-b2217678cbcc/r)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">List of Queries and Tool Calls Made</span>                                                                                \n",
       "\n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Searched local file directory for files related to San Francisco coffee shops and coffee quality.               \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Opened and inspected the file <span style=\"color: #008080; text-decoration-color: #008080; background-color: #000000; font-weight: bold\">coffee_shops_sf.md</span>.                                                               \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Searched for files using keywords \"coffee quality,\" \"review,\" and \"rating.\"                                     \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span>Explored the directory tree for additional files.                                                               \n",
       "\n",
       "<span style=\"font-weight: bold\">Fully Comprehensive Findings</span>                                                                                       \n",
       "\n",
       "From the file <span style=\"color: #008080; text-decoration-color: #008080; background-color: #000000; font-weight: bold\">coffee_shops_sf.md</span>, the following information about notable San Francisco coffee shops was found:    \n",
       "\n",
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃                                       <span style=\"font-weight: bold\">San Francisco Coffee Shops Research</span>                                       ┃\n",
       "┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛\n",
       "\n",
       "\n",
       "                                         <span style=\"font-weight: bold; text-decoration: underline\">Top Coffee Shops in San Francisco</span>                                         \n",
       "\n",
       "                                                <span style=\"font-weight: bold\">Blue Bottle Coffee</span>                                                 \n",
       "\n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Founded</span>: 2002 in Oakland, expanded to SF                                                                        \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Specialty</span>: Single-origin coffee, pour-over methods                                                              \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Notable</span>: Known for freshly roasted beans, minimalist aesthetic                                                  \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Locations</span>: Multiple SF locations including Ferry Building                                                       \n",
       "\n",
       "                                                   <span style=\"font-weight: bold\">Philz Coffee</span>                                                    \n",
       "\n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Founded</span>: 2003 in San Francisco                                                                                  \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Specialty</span>: Custom blended coffee, personalized service                                                          \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Notable</span>: Founded by Phil Jaber, known for unique blends like \"Tesora\"                                           \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Locations</span>: Original location in Mission District, now citywide                                                  \n",
       "\n",
       "                                                 <span style=\"font-weight: bold\">Sightglass Coffee</span>                                                 \n",
       "\n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Founded</span>: 2009                                                                                                   \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Specialty</span>: Third-wave coffee, roasting transparency                                                             \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Notable</span>: Large roastery with viewing windows, industrial aesthetic                                              \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Location</span>: SOMA district flagship location                                                                       \n",
       "\n",
       "                                              <span style=\"font-weight: bold\">Ritual Coffee Roasters</span>                                               \n",
       "\n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Founded</span>: 2005                                                                                                   \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Specialty</span>: Direct trade relationships, seasonal offerings                                                       \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Notable</span>: Pioneer in San Francisco's third-wave coffee movement                                                  \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Locations</span>: Multiple locations including Castro and Mission                                                      \n",
       "\n",
       "                                                <span style=\"font-weight: bold\">Four Barrel Coffee</span>                                                 \n",
       "\n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Founded</span>: 2008                                                                                                   \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Specialty</span>: Small-batch roasting, community focus                                                                \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Notable</span>: Known for Valencia Street location, local institution                                                  \n",
       "<span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\"> • </span><span style=\"font-weight: bold\">Location</span>: Mission District                                                                                      \n",
       "\n",
       "No other local files were found containing quality assessments, reviews, or ratings data. No expert reviews,       \n",
       "specialty coffee certifications, customer ratings, comparative rankings, or quality scores were available. The     \n",
       "findings are solely based on the information contained in <span style=\"color: #008080; text-decoration-color: #008080; background-color: #000000; font-weight: bold\">coffee_shops_sf.md</span>.                                      \n",
       "\n",
       "<span style=\"font-weight: bold\">List of All Relevant Sources (with citations in the report)</span>                                                        \n",
       "\n",
       "[1] coffee_shops_sf.md file (internal data source)                                                                 \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mList of Queries and Tool Calls Made\u001b[0m                                                                                \n",
       "\n",
       "\u001b[1;33m • \u001b[0mSearched local file directory for files related to San Francisco coffee shops and coffee quality.               \n",
       "\u001b[1;33m • \u001b[0mOpened and inspected the file \u001b[1;36;40mcoffee_shops_sf.md\u001b[0m.                                                               \n",
       "\u001b[1;33m • \u001b[0mSearched for files using keywords \"coffee quality,\" \"review,\" and \"rating.\"                                     \n",
       "\u001b[1;33m • \u001b[0mExplored the directory tree for additional files.                                                               \n",
       "\n",
       "\u001b[1mFully Comprehensive Findings\u001b[0m                                                                                       \n",
       "\n",
       "From the file \u001b[1;36;40mcoffee_shops_sf.md\u001b[0m, the following information about notable San Francisco coffee shops was found:    \n",
       "\n",
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃                                       \u001b[1mSan Francisco Coffee Shops Research\u001b[0m                                       ┃\n",
       "┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛\n",
       "\n",
       "\n",
       "                                         \u001b[1;4mTop Coffee Shops in San Francisco\u001b[0m                                         \n",
       "\n",
       "                                                \u001b[1mBlue Bottle Coffee\u001b[0m                                                 \n",
       "\n",
       "\u001b[1;33m • \u001b[0m\u001b[1mFounded\u001b[0m: 2002 in Oakland, expanded to SF                                                                        \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mSpecialty\u001b[0m: Single-origin coffee, pour-over methods                                                              \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mNotable\u001b[0m: Known for freshly roasted beans, minimalist aesthetic                                                  \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mLocations\u001b[0m: Multiple SF locations including Ferry Building                                                       \n",
       "\n",
       "                                                   \u001b[1mPhilz Coffee\u001b[0m                                                    \n",
       "\n",
       "\u001b[1;33m • \u001b[0m\u001b[1mFounded\u001b[0m: 2003 in San Francisco                                                                                  \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mSpecialty\u001b[0m: Custom blended coffee, personalized service                                                          \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mNotable\u001b[0m: Founded by Phil Jaber, known for unique blends like \"Tesora\"                                           \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mLocations\u001b[0m: Original location in Mission District, now citywide                                                  \n",
       "\n",
       "                                                 \u001b[1mSightglass Coffee\u001b[0m                                                 \n",
       "\n",
       "\u001b[1;33m • \u001b[0m\u001b[1mFounded\u001b[0m: 2009                                                                                                   \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mSpecialty\u001b[0m: Third-wave coffee, roasting transparency                                                             \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mNotable\u001b[0m: Large roastery with viewing windows, industrial aesthetic                                              \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mLocation\u001b[0m: SOMA district flagship location                                                                       \n",
       "\n",
       "                                              \u001b[1mRitual Coffee Roasters\u001b[0m                                               \n",
       "\n",
       "\u001b[1;33m • \u001b[0m\u001b[1mFounded\u001b[0m: 2005                                                                                                   \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mSpecialty\u001b[0m: Direct trade relationships, seasonal offerings                                                       \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mNotable\u001b[0m: Pioneer in San Francisco's third-wave coffee movement                                                  \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mLocations\u001b[0m: Multiple locations including Castro and Mission                                                      \n",
       "\n",
       "                                                \u001b[1mFour Barrel Coffee\u001b[0m                                                 \n",
       "\n",
       "\u001b[1;33m • \u001b[0m\u001b[1mFounded\u001b[0m: 2008                                                                                                   \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mSpecialty\u001b[0m: Small-batch roasting, community focus                                                                \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mNotable\u001b[0m: Known for Valencia Street location, local institution                                                  \n",
       "\u001b[1;33m • \u001b[0m\u001b[1mLocation\u001b[0m: Mission District                                                                                      \n",
       "\n",
       "No other local files were found containing quality assessments, reviews, or ratings data. No expert reviews,       \n",
       "specialty coffee certifications, customer ratings, comparative rankings, or quality scores were available. The     \n",
       "findings are solely based on the information contained in \u001b[1;36;40mcoffee_shops_sf.md\u001b[0m.                                      \n",
       "\n",
       "\u001b[1mList of All Relevant Sources (with citations in the report)\u001b[0m                                                        \n",
       "\n",
       "[1] coffee_shops_sf.md file (internal data source)                                                                 \n"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from rich.markdown import Markdown\n",
    "Markdown(result['compressed_research'])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What Just Happened? Let's Understand Each Component\n",
    "\n",
    "#### The Client-Server Architecture\n",
    "\n",
    "**Basic Client-Server Model:**\n",
    "- **Client**: The `MultiServerMCPClient` acts as the client that requests services\n",
    "- **Server**: The MCP server provides tools and executes operations\n",
    "- **Communication**: They communicate using a standardized protocol (MCP)\n",
    "\n",
    "```python\n",
    "client = MultiServerMCPClient(mcp_config)\n",
    "```\n",
    "\n",
    "The `MultiServerMCPClient` is our LangChain MCP adapter client that:\n",
    "- Starts MCP servers based on configuration\n",
    "- Manages communication with one or more servers\n",
    "- Converts MCP protocols to LangChain-compatible formats\n",
    "\n",
    "#### `mcp_config` Dictionary and Transport Types\n",
    "\n",
    "The configuration tells the MCP client how to start and connect to MCP servers:\n",
    "\n",
    "```python\n",
    "mcp_config = {\n",
    "    \"filesystem\": {  # Server name (arbitrary label)\n",
    "        \"command\": \"npx\",  # Command to run\n",
    "        \"args\": [\"-y\", \"@modelcontextprotocol/server-filesystem\", \"/path/to/docs\"],\n",
    "        \"transport\": \"stdio\"  # Communication method\n",
    "    }\n",
    "}\n",
    "```\n",
    "\n",
    "**Configuration Components:**\n",
    "- **Server name** (`\"filesystem\"`): An arbitrary label for this server instance\n",
    "- **Command** (`\"npx\"`): The command to execute to start the server\n",
    "- **Args**: Command-line arguments passed to the server\n",
    "- **Transport**: How the client communicates with the server\n",
    "\n",
    "**Two Transport Types:**\n",
    "\n",
    "1. **stdio Transport** (Local Servers):\n",
    "   - Uses standard input/output for communication\n",
    "   - Server runs as a subprocess on your local machine\n",
    "   - Communication via pipes (stdin/stdout)\n",
    "   - Example: `\"transport\": \"stdio\"`\n",
    "\n",
    "2. **HTTP Transport** (Remote Servers):\n",
    "   - Uses HTTP requests for communication\n",
    "   - Server runs remotely on another machine/service\n",
    "   - Communication via HTTP endpoints\n",
    "   - Example: `\"transport\": \"http\"` with `\"url\": \"https://api.example.com/mcp\"`\n",
    "\n",
    "**Remote MCP Servers:**\n",
    "Remote MCP servers are third-party services that provide tools via HTTP. According to [Anthropic's documentation](https://docs.anthropic.com/en/docs/agents-and-tools/remote-mcp-servers):\n",
    "\n",
    "- Companies like Asana, Cloudflare, PayPal, and Zapier offer remote MCP servers\n",
    "- These use HTTP transport instead of stdio\n",
    "- Typical URL format: `https://mcp.[company-name].com/sse`\n",
    "- Require authentication credentials and trust verification\n",
    "\n",
    "**Example Remote Configuration:**\n",
    "```python\n",
    "mcp_config = {\n",
    "    \"remote_service\": {\n",
    "        \"url\": \"https://mcp.example.com/sse\",\n",
    "        \"transport\": \"http\",\n",
    "        \"headers\": {\n",
    "            \"Authorization\": \"Bearer your-token-here\"\n",
    "        }\n",
    "    }\n",
    "}\n",
    "```\n",
    "\n",
    "#### The Server\n",
    "\n",
    "When using stdio transport (local servers):\n",
    "- Client `MultiServerMCPClient(mcp_config)` starts the server as a subprocess\n",
    "- Server is a Node.js process running on your local machine\n",
    "- It runs: `npx @modelcontextprotocol/server-filesystem /path/to/docs`\n",
    "- The server process runs as long as the client is active\n",
    "- **Verified**: Yes, the client starts and manages the server process lifecycle\n",
    "\n",
    "When using HTTP transport (remote servers):\n",
    "- Client connects to an existing remote server\n",
    "- No subprocess is started locally\n",
    "- Server runs independently on remote infrastructure\n",
    "- Communication happens over HTTP/HTTPS\n",
    "\n",
    "#### Tool Binding\n",
    "\n",
    "Within the agent, MCP client queries the server for tools:\n",
    "```python\n",
    "tools = await client.get_tools()\n",
    "```\n",
    "\n",
    "**The Process:**\n",
    "1. MCP client queries each server: \"What tools do you provide?\"\n",
    "2. Server responds with tool metadata: Name, description, parameters, types\n",
    "3. The MCP client (adapter) converts tool metadata to LangChain format\n",
    "4. This makes them compatible with LangChain agents\n",
    "5. We bind the tools to the model as usual:\n",
    "```python\n",
    "model_with_tools = model.bind_tools(tools)\n",
    "```\n",
    "\n",
    "#### Tool Execution\n",
    "\n",
    "When the LLM calls a tool:\n",
    "1. **LLM Decision**: The LLM decides which tools to use based on the user's request\n",
    "2. **Client Forwarding**: The client forwards the request to the appropriate server\n",
    "3. **Communication**: \n",
    "   - **stdio**: Via STDIN (for local servers)\n",
    "   - **HTTP**: Via HTTP requests (for remote servers)\n",
    "4. **Server Execution**: The server executes the operation (e.g., reads a file)\n",
    "5. **Async Processing**: This is done asynchronously for performance\n",
    "6. **Response**: Server sends responses back to the client\n",
    "   - **stdio**: Via STDOUT (for local servers)\n",
    "   - **HTTP**: Via HTTP responses (for remote servers)\n",
    "7. **Protocol**: All communication uses MCP protocol format (JSON-RPC)\n",
    "\n",
    "```python\n",
    "coros.append(tool.ainvoke(tool_call[\"args\"]))\n",
    "```\n",
    "\n",
    "**Key Differences:**\n",
    "- **Local (stdio)**: Fast, secure, requires server installation\n",
    "- **Remote (HTTP)**: Slower, requires trust/auth, no local installation needed"
   ]
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    "### LangGraph Studio\n",
    "\n",
    "Just as we did before, we can also use LangGraph Studio to visualize the agent. \n",
    "\n",
    "This agent has been added to the `langgraph.json` file, so you can select `research_agent_mcp` in the dropdown menu:\n",
    "\n",
    "```\n",
    "\"research_agent_mcp\": \"./src/deep_research_from_scratch/research_agent_mcp.py:agent\"\n",
    "```\n",
    "\n",
    "Run the following command to start the studio\n",
    "\n",
    "```bash\n",
    "uvx --refresh --from \"langgraph-cli[inmem]\" --with-editable . --python 3.11 langgraph dev --allow-blocking\n",
    "```"
   ]
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